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Top 10 Cloud Computing Research Topics of 2024

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Cloud computing is a fast-growing area in the technical landscape due to its recent developments. If we look ahead to 2024, there are new research topics in cloud computing that are getting more traction among researchers and practitioners. Cloud computing has ranged from new evolutions on security and privacy with the use of AI & ML usage in the Cloud computing for the new cloud-based applications for specific domains or industries. In this article, we will investigate some of the top cloud computing research topics for 2024 and explore what we get most out of it for researchers or cloud practitioners. To master a cloud computing field, we need to check these Cloud Computing online courses .

Why Cloud Computing is Important for Data-driven Business?

The Cloud computing is crucial for data-driven businesses because it provides scalable and cost-effective ways to store and process huge amounts of data. Cloud-based storage and analytical platform helps business to easily access their data whenever required irrespective of where it is located physically. This helps businesses to take good decisions about their products and marketing plans. 

Cloud computing could help businesses to improve their security in terms of data, Cloud providers offer various features such as data encryption and access control to their customers so that they can protect the data as well as from unauthorized access. 

Few benefits of Cloud computing are listed below: 

• Scalability: With Cloud computing we get scalable applications which suits for large scale production systems for Businesses which store and process large sets of data.
• Cost-effectiveness : It is evident that Cloud computing is cost effective solution compared to the traditional on-premises data storage and analytical solutions due to its scaling capacity which leads to saving more IT costs. 
• Security : Cloud providers offer various security features which includes data encryption and access control, that can help businesses to protect their data from unauthorized access.
• Reliability : Cloud providers ensure high reliability to their customers based on their SLA which is useful for the data-driven business to operate 24X7. 

Top 10 Cloud Computing Research Topics

1. neural network based multi-objective evolutionary algorithm for dynamic workflow scheduling in cloud computing.

Cloud computing research topics are getting wider traction in the Cloud Computing field. These topics in the paper suggest a multi-objective evolutionary algorithm (NN-MOEA) based on neural networks for dynamic workflow scheduling in cloud computing. Due to the dynamic nature of cloud resources and the numerous competing objectives that need to be optimized, scheduling workflows in cloud computing is difficult. The NN-MOEA algorithm utilizes neural networks to optimize multiple objectives, such as planning, cost, and resource utilization. This research focuses on cloud computing and its potential to enhance the efficiency and effectiveness of businesses' cloud-based workflows.

The algorithm predicts workflow completion time using a feedforward neural network based on input and output data sizes and cloud resources. It generates a balanced schedule by taking into account conflicting objectives and projected execution time. It also includes an evolutionary algorithm for future improvement.

The proposed NN-MOEA algorithm has several benefits, such as the capacity to manage dynamic changes in cloud resources and the capacity to simultaneously optimize multiple objectives. The algorithm is also capable of handling a variety of workflows and is easily expandable to include additional goals. The algorithm's use of neural networks to forecast task execution times is a crucial component because it enables the algorithm to generate better schedules and more accurate predictions.

The paper concludes by presenting a novel multi-objective evolutionary algorithm-based neural network-based approach to dynamic workflow scheduling in cloud computing. In terms of optimizing multiple objectives, such as make span and cost, and achieving a better balance between them, these cloud computing dissertation topics on the proposed NN-MOEA algorithm exhibit encouraging results.

Key insights and Research Ideas:

Investigate the use of different neural network architectures for predicting the future positions of optimal solutions. Explore the use of different multi-objective evolutionary algorithms for solving dynamic workflow scheduling problems. Develop a cloud-based workflow scheduling platform that implements the proposed algorithm and makes it available to researchers and practitioners.

2. A systematic literature review on cloud computing security: threats and mitigation strategies 

This is one of cloud computing security research topics in the cloud computing paradigm. The authors then provide a systematic literature review of studies that address security threats to cloud computing and mitigation techniques and were published between 2010 and 2020. They list and classify the risks and defense mechanisms covered in the literature, as well as the frequency and distribution of these subjects over time.

The paper suggests the data breaches, Insider threats and DDoS attack are most discussed threats to the security of cloud computing. Identity and access management, encryption, and intrusion detection and prevention systems are the mitigation techniques that are most frequently discussed. Authors depict the future trends of machine learning and artificial intelligence might help cloud computing to mitigate its risks. 

The paper offers a thorough overview of security risks and mitigation techniques in cloud computing, and it emphasizes the need for more research and development in this field to address the constantly changing security issues with cloud computing. This research could help businesses to reduce the amount of spam that they receive in their cloud-based email systems.

Explore the use of blockchain technology to improve the security of cloud computing systems. Investigate the use of machine learning and artificial intelligence to detect and prevent cloud computing attacks. Develop new security tools and technologies for cloud computing environments. 

3. Spam Identification in Cloud Computing Based on Text Filtering System

A text filtering system is suggested in the paper "Spam Identification in Cloud Computing Based on Text Filtering System" to help identify spam emails in cloud computing environments. Spam emails are a significant issue in cloud computing because they can use up computing resources and jeopardize the system's security. 

To detect spam emails, the suggested system combines text filtering methods with machine learning algorithms. The email content is first pre-processed by the system, which eliminates stop words and stems the remaining words. The preprocessed text is then subjected to several filters, including a blacklist filter and a Bayesian filter, to identify spam emails.

In order to categorize emails as spam or non-spam based on their content, the system also employs machine learning algorithms like decision trees and random forests. The authors use a dataset of emails gathered from a cloud computing environment to train and test the system. They then assess its performance using metrics like precision, recall, and F1 score.

The findings demonstrate the effectiveness of the proposed system in detecting spam emails, achieving high precision and recall rates. By contrasting their system with other spam identification systems, the authors also show how accurate and effective it is. 

The method presented in the paper for locating spam emails in cloud computing environments has the potential to improve the overall security and performance of cloud computing systems. This is one of the interesting clouds computing current research topics to explore and innovate. This is one of the good Cloud computing research topics to protect the Mail threats. 

Create a stronger spam filtering system that can recognize spam emails even when they are made to avoid detection by more common spam filters. examine the application of artificial intelligence and machine learning to the evaluation of spam filtering system accuracy. Create a more effective spam filtering system that can handle a lot of emails quickly and accurately.

4. Blockchain data-based cloud data integrity protection mechanism 

The "Blockchain data-based cloud data integrity protection mechanism" paper suggests a method for safeguarding the integrity of cloud data and which is one of the Cloud computing research topics. In order to store and process massive amounts of data, cloud computing has grown in popularity, but issues with data security and integrity still exist. For the proposed mechanism to guarantee the availability and integrity of cloud data, data redundancy and blockchain technology are combined.

A data redundancy layer, a blockchain layer, and a verification and recovery layer make up the mechanism. For availability in the event of server failure, the data redundancy layer replicates the cloud data across multiple cloud servers. The blockchain layer stores the metadata (such as access rights) and hash values of the cloud data and access control information

Using a dataset of cloud data, the authors assess the performance of the suggested mechanism and compare it to other cloud data protection mechanisms. The findings demonstrate that the suggested mechanism offers high levels of data availability and integrity and is superior to other mechanisms in terms of processing speed and storage space.

Overall, the paper offers a promising strategy for using blockchain technology to guarantee the availability and integrity of cloud data. The suggested mechanism may assist in addressing cloud computing's security issues and enhancing the dependability of cloud data processing and storage. This research could help businesses to protect the integrity of their cloud-based data from unauthorized access and manipulation.

Create a data integrity protection system based on blockchain that is capable of detecting and preventing data tampering in cloud computing environments. For enhancing the functionality and scalability of blockchain-based data integrity protection mechanisms, look into the use of various blockchain consensus algorithms. Create a data integrity protection system based on blockchain that is compatible with current cloud computing platforms. Create a safe and private data integrity protection system based on blockchain technology.

5. A survey on internet of things and cloud computing for healthcare

This article suggests how recent tech trends like the Internet of Things (IoT) and cloud computing could transform the healthcare industry. It is one of the Cloud computing research topics. These emerging technologies open exciting possibilities by enabling remote patient monitoring, personalized care, and efficient data management. This topic is one of the IoT and cloud computing research papers which aims to share a wider range of information. 

The authors categorize the research into IoT-based systems, cloud-based systems, and integrated systems using both IoT and the cloud. They discussed the pros of real-time data collection, improved care coordination, automated diagnosis and treatment.

However, the authors also acknowledge concerns around data security, privacy, and the need for standardized protocols and platforms. Widespread adoption of these technologies faces challenges in ensuring they are implemented responsibly and ethically. To begin the journey KnowledgeHut’s Cloud Computing online course s are good starter for beginners so that they can cope with Cloud computing with IOT. 

Overall, the paper provides a comprehensive overview of this rapidly developing field, highlighting opportunities to revolutionize how healthcare is delivered. New devices, systems and data analytics powered by IoT, and cloud computing could enable more proactive, preventative and affordable care in the future. But careful planning and governance will be crucial to maximize the value of these technologies while mitigating risks to patient safety, trust and autonomy. This research could help businesses to explore the potential of IoT and cloud computing to improve healthcare delivery.

Examine how IoT and cloud computing are affecting patient outcomes in various healthcare settings, including hospitals, clinics, and home care. Analyze how well various IoT devices and cloud computing platforms perform in-the-moment patient data collection, archival, and analysis. assessing the security and privacy risks connected to IoT devices and cloud computing in the healthcare industry and developing mitigation strategies.

6. Targeted influence maximization based on cloud computing over big data in social networks

Big data in cloud computing research papers are having huge visibility in the industry. The paper "Targeted Influence Maximization based on Cloud Computing over Big Data in Social Networks" proposes a targeted influence maximization algorithm to identify the most influential users in a social network. Influence maximization is the process of identifying a group of users in a social network who can have a significant impact or spread information. 

A targeted influence maximization algorithm is suggested in the paper "Targeted Influence maximization based on Cloud Computing over Big Data in Social Networks" to find the most influential users in a social network. The process of finding a group of users in a social network who can make a significant impact or spread information is known as influence maximization.

Four steps make up the suggested algorithm: feature extraction, classification, influence maximization, and data preprocessing. The authors gather and preprocess social network data, such as user profiles and interaction data, during the data preprocessing stage. Using machine learning methods like text mining and sentiment analysis, they extract features from the data during the feature extraction stage. Overall, the paper offers a promising strategy for maximizing targeted influence using big data and Cloud computing research topics to look into. The suggested algorithm could assist companies and organizations in pinpointing their marketing or communication strategies to reach the most influential members of a social network.

Key insights and Research Ideas: 

Develop a cloud-based targeted influence maximization algorithm that can effectively identify and influence a small number of users in a social network to achieve a desired outcome. Investigate the use of different cloud computing platforms to improve the performance and scalability of cloud-based targeted influence maximization algorithms. Develop a cloud-based targeted influence maximization algorithm that is compatible with existing social network platforms. Design a cloud-based targeted influence maximization algorithm that is secure and privacy-preserving.

7. Security and privacy protection in cloud computing: Discussions and challenges

Cloud computing current research topics are getting traction, this is of such topic which provides an overview of the challenges and discussions surrounding security and privacy protection in cloud computing. The authors highlight the importance of protecting sensitive data in the cloud, with the potential risks and threats to data privacy and security. The article explores various security and privacy issues that arise in cloud computing, including data breaches, insider threats, and regulatory compliance.

The article explores challenges associated with implementing these security measures and highlights the need for effective risk management strategies. Azure Solution Architect Certification course is suitable for a person who needs to work on Azure cloud as an architect who will do system design with keep security in mind. 

Final take away of cloud computing thesis paper by an author points out by discussing some of the emerging trends in cloud security and privacy, including the use of artificial intelligence and machine learning to enhance security, and the emergence of new regulatory frameworks designed to protect data in the cloud and is one of the Cloud computing research topics to keep an eye in the security domain. 

Develop a more comprehensive security and privacy framework for cloud computing. Explore the options with machine learning and artificial intelligence to enhance the security and privacy of cloud computing. Develop more robust security and privacy mechanisms for cloud computing. Design security and privacy policies for cloud computing that are fair and transparent. Educate cloud users about security and privacy risks and best practices.

8. Intelligent task prediction and computation offloading based on mobile-edge cloud computing

This Cloud Computing thesis paper "Intelligent Task Prediction and Computation Offloading Based on Mobile-Edge Cloud Computing" proposes a task prediction and computation offloading mechanism to improve the performance of mobile applications under the umbrella of cloud computing research ideas.

An algorithm for offloading computations and a task prediction model makes up the two main parts of the suggested mechanism. Based on the mobile application's usage patterns, the task prediction model employs machine learning techniques to forecast its upcoming tasks. This prediction is to decide whether to execute a specific task locally on the mobile device or offload the computation of it to the cloud.

Using a dataset of mobile application usage patterns, the authors assess the performance of the suggested mechanism and compare it to other computation offloading mechanisms. The findings demonstrate that the suggested mechanism performs better in terms of energy usage, response time, and network usage.

The authors also go over the difficulties in putting the suggested mechanism into practice, including the need for real-time task prediction and the trade-off between offloading computation and network usage. Additionally, they outline future research directions for mobile-edge cloud computing applications, including the use of edge caching and the integration of blockchain technology for security and privacy. 

Overall, the paper offers a promising strategy for enhancing mobile application performance through mobile-edge cloud computing. The suggested mechanism might improve the user experience for mobile users while lowering the energy consumption and response time of mobile applications. These Cloud computing dissertation topic leads to many innovation ideas. 

Develop an accurate task prediction model considering mobile device and cloud dynamics. Explore machine learning and AI for efficient computation offloading. Create a robust framework for diverse tasks and scenarios. Design a secure, privacy-preserving computation offloading mechanism. Assess computation offloading effectiveness in real-world mobile apps.

9. Cloud Computing and Security: The Security Mechanism and Pillars of ERPs on Cloud Technology

Enterprise resource planning (ERP) systems are one of the Cloud computing research topics in particular face security challenges with cloud computing, and the paper "Cloud Computing and Security: The Security Mechanism and Pillars of ERPs on Cloud Technology" discusses these challenges and suggests a security mechanism and pillars for protecting ERP systems on cloud technology.

The authors begin by going over the benefits of ERP systems and cloud computing as well as the security issues with cloud computing, like data breaches and insider threats. They then go on to present a security framework for cloud-based ERP systems that is built around four pillars: access control, data encryption, data backup and recovery, and security monitoring. The access control pillar restricts user access, while the data encryption pillar secures sensitive data. Data backup and recovery involve backing up lost or failed data. Security monitoring continuously monitors the ERP system for threats. The authors also discuss interoperability challenges and the need for standardization in securing ERP systems on the cloud. They propose future research directions, such as applying machine learning and artificial intelligence to security analytics.

Overall, the paper outlines a thorough strategy for safeguarding ERP systems using cloud computing and emphasizes the significance of addressing security issues related to this technology. Organizations can protect their ERP systems and make sure the Security as well as privacy of their data by implementing these security pillars and mechanisms. 

Investigate the application of blockchain technology to enhance the security of cloud-based ERP systems. Look into the use of machine learning and artificial intelligence to identify and stop security threats in cloud-based ERP systems. Create fresh security measures that are intended only for cloud-based ERP systems. By more effectively managing access control and data encryption, cloud-based ERP systems can be made more secure. Inform ERP users about the security dangers that come with cloud-based ERP systems and how to avoid them.

10. Optimized data storage algorithm of IoT based on cloud computing in distributed system

The article proposes an optimized data storage algorithm for Internet of Things (IoT) devices which runs on cloud computing in a distributed system. In IoT apps, which normally generate huge amounts of data by various devices, the algorithm tries to increase the data storage and faster retrials of the same. 

The algorithm proposed includes three main components: Data Processing, Data Storage, and Data Retrieval. The Data Processing module preprocesses IoT device data by filtering or compressing it. The Data Storage module distributes the preprocessed data across cloud servers using partitioning and stores it in a distributed database. The Data Retrieval module efficiently retrieves stored data in response to user queries, minimizing data transmission and enhancing query efficiency. The authors evaluated the algorithm's performance using an IoT dataset and compared it to other storage and retrieval algorithms. Results show that the proposed algorithm surpasses others in terms of storage effectiveness, query response time, and network usage. 

They suggest future directions such as leveraging edge computing and blockchain technology for optimizing data storage and retrieval in IoT applications. In conclusion, the paper introduces a promising method to improve data archival and retrieval in distributed cloud based IoT applications, enhancing the effectiveness and scalability of IoT applications.

Create a data storage algorithm capable of storing and managing large amounts of IoT data efficiently. Examine the use of cloud computing to improve the performance and scalability of data storage algorithms for IoT. Create a secure and privacy-preserving data storage algorithm. Assess the performance and effectiveness of data storage algorithms for IoT in real-world applications.

How to Write a Perfect Research Paper?

• Choose a topic: Select the topic which is interesting to you so that you can share things with the viewer seamlessly with good content. 
• Do your research: Read books, articles, and websites on your topic. Take notes and gather evidence to support your arguments.
• Write an outline: This will help you organize your thoughts and make sure your paper flows smoothly.
• Start your paper: Start with an introduction that grabs the reader's attention. Then, state your thesis statement and support it with evidence from your research. Finally, write a conclusion that summarizes your main points.
• Edit and proofread your paper. Make sure you check the grammatical errors and spelling mistakes. 

Cloud computing is a rapidly evolving area with more interesting research topics being getting traction by researchers and practitioners. Cloud providers have their research to make sure their customer data is secured and take care of their security which includes encryption algorithms, improved access control and mitigating DDoS – Deniel of Service attack etc., 

With the improvements in AI & ML, a few features developed to improve the performance, efficiency, and security of cloud computing systems. Some of the research topics in this area include developing new algorithms for resource allocation, optimizing cloud workflows, and detecting and mitigating cyberattacks.

Cloud computing is being used in industries such as healthcare, finance, and manufacturing. Some of the research topics in this area include developing new cloud-based medical imaging applications, building cloud-based financial trading platforms, and designing cloud-based manufacturing systems.

Frequently Asked Questions (FAQs)

Data security and privacy problems, vendor lock-in, complex cloud management, a lack of standardization, and the risk of service provider disruptions are all current issues in cloud computing. Because data is housed on third-party servers, data security and privacy are key considerations. Vendor lock-in makes transferring providers harder and increases reliance on a single one. Managing many cloud services complicates things. Lack of standardization causes interoperability problems and restricts workload mobility between providers. 

Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) are the cloud computing scenarios where industries focusing right now. 

The six major components of cloud infrastructure are compute, storage, networking, security, management and monitoring, and database. These components enable cloud-based processing and execution, data storage and retrieval, communication between components, security measures, management and monitoring of the infrastructure, and database services.  

Vinoth Kumar P

Vinoth Kumar P is a Cloud DevOps Engineer at Amadeus Labs. He has over 7 years of experience in the IT industry, and is specialized in DevOps, GitOps, DevSecOps, MLOps, Chaos Engineering, Cloud and Cloud Native landscapes. He has published articles and blogs on recent tech trends and best practices on GitHub, Medium, and LinkedIn, and has delivered a DevSecOps 101 talk to Developers community , GitOps with Argo CD Webinar for DevOps Community. He has helped multiple enterprises with their cloud migration, cloud native design, CICD pipeline setup, and containerization journey.

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Cloud computing has suddenly seen a spike in employment opportunities around the globe with tech giants like Amazon, Google, and Microsoft hiring people for their cloud infrastructure. Before the onset of cloud computing, companies and businesses had to set up their own data centers, allocate resources and other IT professionals thereby increasing the cost. The rapid development of the cloud has led to more flexibility, cost-cutting, and scalability. 

The Cloud Computing market its an all-time high with the current market size at USD 371.4 billion and is expected to grow up to USD 832.1 billion by 2025! It’s quickly evolving and gradually realizing its business value along with attracting more and more researchers, scholars, computer scientists, and practitioners. Cloud computing is not a single topic but a composition of various techniques which together constitute the cloud. Below are 10 the most demanded research topics in the field of cloud computing:

1. Big Data

Big data refers to the large amounts of data produced by various programs in a very short duration of time. It is quite cumbersome to store such huge and voluminous amounts of data in company-run data centers. Also, gaining insights from this data becomes a tedious task and takes a lot of time to run and provide results, therefore cloud is the best option. All the data can be pushed onto the cloud without the need for physical storage devices that are to be managed and secured. Also, some popular public clouds provide comprehensive big data platforms to turn data into actionable insights. 

DevOps is an amalgamation of two terms, Development and Operations. It has led to Continuous Delivery, Integration, and Deployment and therefore reducing boundaries between the development team and the operations team. Heavy applications and software need elaborate and complex tech stacks that demand extensive labor to develop and configure which can easily be eliminated by cloud computing. It offers a wide range of tools and technologies to build, test, and deploy applications with a few minutes and a single click. They can be customized as per the client requirements and can be discarded when not in use hence making the process seamless and cost-efficient for development teams.

3. Cloud Cryptography

Data in the cloud is needed to be protected and secured from foreign attacks and breaches. To accomplish this, cryptography in the cloud is a widely used technique to secure data present in the cloud. It allows users and clients to easily and reliably access the shared cloud services since all the data is secured using either the encryption techniques or by using the concept of the private key. It can make the plain text unreadable and limits the view of the data being transferred. Best cloud cryptographic security techniques are the ones that do not compromise the speed of data transfer and provide security without delaying the exchange of sensitive data. 

4. Cloud Load Balancing

It refers to splitting and distributing the incoming load to the server from various sources. It permits companies and organizations to govern and supervise workload demands or application demands by redistributing, reallocating, and administering resources between different computers, networks, or servers. Cloud load balancing encompasses holding the circulation of traffic and demands that exist over the Internet. This reduces the problem of sudden outages, results in an improvement in overall performance, has rare chances of server crashes, and also provides an advanced level of security. Cloud-based servers farms can accomplish more precise scalability and accessibility using the server load balancing mechanism. Due to this, the workload demands can be easily distributed and controlled.

5. Mobile Cloud Computing

It is a mixture of cloud computing, mobile computing, and wireless network to provide services such as seamless and abundant computational resources to mobile users, network operators, and cloud computing professionals. The handheld device is the console and all the processing and data storage takes place outside the physical mobile device. Some advantages of using mobile cloud computing are that there is no need for costly hardware, battery life is longer, extended data storage capacity and processing power improved synchronization of data and high availability due to “store in one place, accessible from anywhere”. The integration and security aspects are taken care of by the backend that enables support to an abundance of access methods. 

6. Green Cloud Computing

The major challenge in the cloud is the utilization of energy-efficient and hence develop economically friendly cloud computing solutions. Data centers that include servers, cables, air conditioners, networks, etc. in large numbers consume a lot of power and release enormous quantities of Carbon Dioxide in the atmosphere. Green Cloud Computing focuses on making virtual data centers and servers to be more environmentally friendly and energy-efficient. Cloud resources often consume so much power and energy leading to a shortage of energy and affecting the global climate. Green cloud computing provides solutions to make such resources more energy efficient and to reduce operational costs. This pivots on power management, virtualization of servers and data centers, recycling vast e-waste, and environmental sustainability. 

7. Edge Computing

It is the advancement and a much more efficient form of Cloud computing with the idea that the data is processed nearer to the source. Edge Computing states that all of the computation will be carried out at the edge of the network itself rather than on a centrally managed platform or the data warehouses. Edge computing distributes various data processing techniques and mechanisms across different positions. This makes the data deliverable to the nearest node and the processing at the edge. This also increases the security of the data since it is closer to the source and eliminates late response time and latency without affecting productivity.

8. Containerization

Containerization in cloud computing is a procedure to obtain operating system virtualization. The user can work with a program and its dependencies utilizing remote resource procedures. The container in cloud computing is used to construct blocks, which aid in producing operational effectiveness, version control, developer productivity, and environmental stability. The infrastructure is upgraded since it provides additional control over the granular activities over the resources. The usage of containers in online services assists storage with cloud computing data security, elasticity, and availability. Containers provide certain advantages such as a steady runtime environment, the ability to run virtually anywhere, and the low overhead compared to virtual machines. 

9. Cloud Deployment Model

There are four main cloud deployment models namely public cloud, private cloud, hybrid cloud, and community cloud. Each deployment model is defined as per the location of the infrastructure. The public cloud allows systems and services to be easily accessible to the general public. Public cloud could also be less reliable since it is open to everyone e.g. Email. A private cloud allows systems and services to be accessible inside an organization with no access to outsiders. It offers better security due to its access restrictions. Hybrid cloud is a mixture of private and public clouds with the critical activities being performed using private cloud and non-critical activities being performed using the public cloud. Community cloud allows system and services to be accessible by a group of an organization.

10. Cloud Security

Since the number of companies and organizations using cloud computing is increasing at a rapid rate, the security of the cloud is a major concern. Cloud computing security detects and addresses every physical and logical security issue that comes across all the varied service models of code, platform, and infrastructure. It collectively addresses these services, however, these services are delivered in units, that is, the public, private, or hybrid delivery model. Security in the cloud protects the data from any leakage or outflow, theft, calamity, and removal. With the help of tokenization, Virtual Private Networks, and firewalls data can be secured. 

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Hardware-accelerated cloud computing systems based on FPGA chips (FPGA cloud) or ASIC chips (ASIC cloud) have emerged as a new technology trend for power-efficient acceleration of various software applications. However, the operating systems and hypervisors currently used in cloud computing will lead to power, performance, and scalability problems in an exascale cloud computing environment. Consequently, the present study proposes a parallel hardware hypervisor system that is implemented entirely in special-purpose hardware, and that virtualizes application-specific multi-chip supercomputers, to enable virtual supercomputers to share available FPGA and ASIC resources in a cloud system. In addition to the virtualization of multi-chip supercomputers, the system’s other unique features include simultaneous migration of multiple communicating hardware tasks, and on-demand increase or decrease of hardware resources allocated to a virtual supercomputer. Partitioning the flat hardware design of the proposed hypervisor system into multiple partitions and applying the chip unioning technique to its partitions, the present study introduces a cloud building block chip that can be used to create FPGA or ASIC clouds as well. Single-chip and multi-chip verification studies have been done to verify the functional correctness of the hypervisor system, which consumes only a fraction of (10%) hardware resources.

Study On Social Network Recommendation Service Method Based On Mobile Cloud Computing

Cloud-based network virtualization in iot with openstack.

In Cloud computing deployments, specifically in the Infrastructure-as-a-Service (IaaS) model, networking is one of the core enabling facilities provided for the users. The IaaS approach ensures significant flexibility and manageability, since the networking resources and topologies are entirely under users’ control. In this context, considerable efforts have been devoted to promoting the Cloud paradigm as a suitable solution for managing IoT environments. Deep and genuine integration between the two ecosystems, Cloud and IoT, may only be attainable at the IaaS level. In light of extending the IoT domain capabilities’ with Cloud-based mechanisms akin to the IaaS Cloud model, network virtualization is a fundamental enabler of infrastructure-oriented IoT deployments. Indeed, an IoT deployment without networking resilience and adaptability makes it unsuitable to meet user-level demands and services’ requirements. Such a limitation makes the IoT-based services adopted in very specific and statically defined scenarios, thus leading to limited plurality and diversity of use cases. This article presents a Cloud-based approach for network virtualization in an IoT context using the de-facto standard IaaS middleware, OpenStack, and its networking subsystem, Neutron. OpenStack is being extended to enable the instantiation of virtual/overlay networks between Cloud-based instances (e.g., virtual machines, containers, and bare metal servers) and/or geographically distributed IoT nodes deployed at the network edge.

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Research Topics & Ideas: CompSci & IT

50+ Computer Science Research Topic Ideas To Fast-Track Your Project

Finding and choosing a strong research topic is the critical first step when it comes to crafting a high-quality dissertation, thesis or research project. If you’ve landed on this post, chances are you’re looking for a computer science-related research topic , but aren’t sure where to start. Here, we’ll explore a variety of CompSci & IT-related research ideas and topic thought-starters, including algorithms, AI, networking, database systems, UX, information security and software engineering.

NB – This is just the start…

The topic ideation and evaluation process has multiple steps . In this post, we’ll kickstart the process by sharing some research topic ideas within the CompSci domain. This is the starting point, but to develop a well-defined research topic, you’ll need to identify a clear and convincing research gap , along with a well-justified plan of action to fill that gap.

If you’re new to the oftentimes perplexing world of research, or if this is your first time undertaking a formal academic research project, be sure to check out our free dissertation mini-course. In it, we cover the process of writing a dissertation or thesis from start to end. Be sure to also sign up for our free webinar that explores how to find a high-quality research topic. 

Overview: CompSci Research Topics

• Algorithms & data structures
• Artificial intelligence ( AI )
• Computer networking
• Database systems
• Human-computer interaction
• Information security (IS)
• Software engineering
• Examples of CompSci dissertation & theses

Topics/Ideas: Algorithms & Data Structures

• An analysis of neural network algorithms’ accuracy for processing consumer purchase patterns
• A systematic review of the impact of graph algorithms on data analysis and discovery in social media network analysis
• An evaluation of machine learning algorithms used for recommender systems in streaming services
• A review of approximation algorithm approaches for solving NP-hard problems
• An analysis of parallel algorithms for high-performance computing of genomic data
• The influence of data structures on optimal algorithm design and performance in Fintech
• A Survey of algorithms applied in internet of things (IoT) systems in supply-chain management
• A comparison of streaming algorithm performance for the detection of elephant flows
• A systematic review and evaluation of machine learning algorithms used in facial pattern recognition
• Exploring the performance of a decision tree-based approach for optimizing stock purchase decisions
• Assessing the importance of complete and representative training datasets in Agricultural machine learning based decision making.
• A Comparison of Deep learning algorithms performance for structured and unstructured datasets with “rare cases”
• A systematic review of noise reduction best practices for machine learning algorithms in geoinformatics.
• Exploring the feasibility of applying information theory to feature extraction in retail datasets.
• Assessing the use case of neural network algorithms for image analysis in biodiversity assessment

Topics & Ideas: Artificial Intelligence (AI)

• Applying deep learning algorithms for speech recognition in speech-impaired children
• A review of the impact of artificial intelligence on decision-making processes in stock valuation
• An evaluation of reinforcement learning algorithms used in the production of video games
• An exploration of key developments in natural language processing and how they impacted the evolution of Chabots.
• An analysis of the ethical and social implications of artificial intelligence-based automated marking
• The influence of large-scale GIS datasets on artificial intelligence and machine learning developments
• An examination of the use of artificial intelligence in orthopaedic surgery
• The impact of explainable artificial intelligence (XAI) on transparency and trust in supply chain management
• An evaluation of the role of artificial intelligence in financial forecasting and risk management in cryptocurrency
• A meta-analysis of deep learning algorithm performance in predicting and cyber attacks in schools

Topics & Ideas: Networking

• An analysis of the impact of 5G technology on internet penetration in rural Tanzania
• Assessing the role of software-defined networking (SDN) in modern cloud-based computing
• A critical analysis of network security and privacy concerns associated with Industry 4.0 investment in healthcare.
• Exploring the influence of cloud computing on security risks in fintech.
• An examination of the use of network function virtualization (NFV) in telecom networks in Southern America
• Assessing the impact of edge computing on network architecture and design in IoT-based manufacturing
• An evaluation of the challenges and opportunities in 6G wireless network adoption
• The role of network congestion control algorithms in improving network performance on streaming platforms
• An analysis of network coding-based approaches for data security
• Assessing the impact of network topology on network performance and reliability in IoT-based workspaces

Topics & Ideas: Database Systems

• An analysis of big data management systems and technologies used in B2B marketing
• The impact of NoSQL databases on data management and analysis in smart cities
• An evaluation of the security and privacy concerns of cloud-based databases in financial organisations
• Exploring the role of data warehousing and business intelligence in global consultancies
• An analysis of the use of graph databases for data modelling and analysis in recommendation systems
• The influence of the Internet of Things (IoT) on database design and management in the retail grocery industry
• An examination of the challenges and opportunities of distributed databases in supply chain management
• Assessing the impact of data compression algorithms on database performance and scalability in cloud computing
• An evaluation of the use of in-memory databases for real-time data processing in patient monitoring
• Comparing the effects of database tuning and optimization approaches in improving database performance and efficiency in omnichannel retailing

Topics & Ideas: Human-Computer Interaction

• An analysis of the impact of mobile technology on human-computer interaction prevalence in adolescent men
• An exploration of how artificial intelligence is changing human-computer interaction patterns in children
• An evaluation of the usability and accessibility of web-based systems for CRM in the fast fashion retail sector
• Assessing the influence of virtual and augmented reality on consumer purchasing patterns
• An examination of the use of gesture-based interfaces in architecture
• Exploring the impact of ease of use in wearable technology on geriatric user
• Evaluating the ramifications of gamification in the Metaverse
• A systematic review of user experience (UX) design advances associated with Augmented Reality
• A comparison of natural language processing algorithms automation of customer response Comparing end-user perceptions of natural language processing algorithms for automated customer response
• Analysing the impact of voice-based interfaces on purchase practices in the fast food industry

Topics & Ideas: Information Security

• A bibliometric review of current trends in cryptography for secure communication
• An analysis of secure multi-party computation protocols and their applications in cloud-based computing
• An investigation of the security of blockchain technology in patient health record tracking
• A comparative study of symmetric and asymmetric encryption algorithms for instant text messaging
• A systematic review of secure data storage solutions used for cloud computing in the fintech industry
• An analysis of intrusion detection and prevention systems used in the healthcare sector
• Assessing security best practices for IoT devices in political offices
• An investigation into the role social media played in shifting regulations related to privacy and the protection of personal data
• A comparative study of digital signature schemes adoption in property transfers
• An assessment of the security of secure wireless communication systems used in tertiary institutions

Topics & Ideas: Software Engineering

• A study of agile software development methodologies and their impact on project success in pharmacology
• Investigating the impacts of software refactoring techniques and tools in blockchain-based developments
• A study of the impact of DevOps practices on software development and delivery in the healthcare sector
• An analysis of software architecture patterns and their impact on the maintainability and scalability of cloud-based offerings
• A study of the impact of artificial intelligence and machine learning on software engineering practices in the education sector
• An investigation of software testing techniques and methodologies for subscription-based offerings
• A review of software security practices and techniques for protecting against phishing attacks from social media
• An analysis of the impact of cloud computing on the rate of software development and deployment in the manufacturing sector
• Exploring the impact of software development outsourcing on project success in multinational contexts
• An investigation into the effect of poor software documentation on app success in the retail sector

CompSci & IT Dissertations/Theses

While the ideas we’ve presented above are a decent starting point for finding a CompSci-related research topic, they are fairly generic and non-specific. So, it helps to look at actual dissertations and theses to see how this all comes together.

Below, we’ve included a selection of research projects from various CompSci-related degree programs to help refine your thinking. These are actual dissertations and theses, written as part of Master’s and PhD-level programs, so they can provide some useful insight as to what a research topic looks like in practice.

• An array-based optimization framework for query processing and data analytics (Chen, 2021)
• Dynamic Object Partitioning and replication for cooperative cache (Asad, 2021)
• Embedding constructural documentation in unit tests (Nassif, 2019)
• PLASA | Programming Language for Synchronous Agents (Kilaru, 2019)
• Healthcare Data Authentication using Deep Neural Network (Sekar, 2020)
• Virtual Reality System for Planetary Surface Visualization and Analysis (Quach, 2019)
• Artificial neural networks to predict share prices on the Johannesburg stock exchange (Pyon, 2021)
• Predicting household poverty with machine learning methods: the case of Malawi (Chinyama, 2022)
• Investigating user experience and bias mitigation of the multi-modal retrieval of historical data (Singh, 2021)
• Detection of HTTPS malware traffic without decryption (Nyathi, 2022)
• Redefining privacy: case study of smart health applications (Al-Zyoud, 2019)
• A state-based approach to context modeling and computing (Yue, 2019)
• A Novel Cooperative Intrusion Detection System for Mobile Ad Hoc Networks (Solomon, 2019)
• HRSB-Tree for Spatio-Temporal Aggregates over Moving Regions (Paduri, 2019)

Looking at these titles, you can probably pick up that the research topics here are quite specific and narrowly-focused , compared to the generic ones presented earlier. This is an important thing to keep in mind as you develop your own research topic. That is to say, to create a top-notch research topic, you must be precise and target a specific context with specific variables of interest . In other words, you need to identify a clear, well-justified research gap.

Fast-Track Your Research Topic

If you’re still feeling a bit unsure about how to find a research topic for your Computer Science dissertation or research project, check out our Topic Kickstarter service.

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Investigating the impacts of software refactoring techniques and tools in blockchain-based developments.

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Latest Research Topics on Cloud Computing (2022 Updated)

Cloud computing is now a vital online technology that is used worldwide. The market size of cloud computing is expected to reach $832.1 billion by 2025 . Its demand will always increase in the future, and there are many major reasons behind it. It has acquired popularity because it is less expensive for companies rather than setting up their on-site server implementations.

In this article, we’ve covered the top 14 in-demand research topics on cloud computing that you need to know.

📌 These cloud Computing research topics are:

• Green cloud computing
• Edge computing
• Cloud cryptography
• Load balancing
• Cloud analytics
• Cloud scalability
• Mobile cloud computing
• Cloud deployment model
• Cloud security
• Cloud computing platforms
• Cloud service model
• Containerization

Top 14 Cloud Computing Research Topics For 2022

1. green cloud computing.

Due to rapid growth and demand for cloud, the energy consumption in data centers is increasing. Green Cloud Computing is used to minimize energy consumption and helps to achieve efficient processing and reduce the generation of E-waste.

 It is also called GREEN IT. The goal is to go paperless and decrease the carbon footprint in the environment due to remote working.

Power management, virtualization, sustainability, and environmental recycling will all be handled by green cloud computing. 

2. Edge Computing

A rapidly growing field where the data is processed at the network’s edge instead of being processed in a data warehouse is known as edge computing. The real-time computing capacity is driving the development of edge-computing platforms. The data is processed from the device itself to the point of origin without relying on a central location which also helps to increase the system’s security. It gives certain benefits such as cost-effectiveness, powerful performance, and new functionality which wasn’t previously available.

Some innovations are made with the help of cloud computing by increasing the ability of network edge capabilities and expanding wireless connections.

3. Cloud Cryptography

Cloud Cryptography is a strong layer of protection through codes that helps to give security to the cloud storage and breach of the data. It saves sensitive data content without delaying the transmission of information. It can turn plain text into unreadable code with the help of computers and algorithms and restrict the view of data being delivered.

The clients can use the cryptographic keys only to access this data. The user’s information is kept private, which results in fewer chances of cybercrime from the hackers. 

4. Load Balancing

The workload distribution over the server for soft computing is called load balancing. It helps distribute resources over multiple PCs, networks, and servers and allows businesses to manage workloads and application needs. Due to the rapid increase in traffic over the Internet, the server gets overloaded—two ways to solve the problem of overload of the servers: single-server and multiple-server solutions.

Keeping the system stable, boosting the system’s efficiency, and avoiding system failures are some reasons to use load balancing. It can be balanced by using software-based and hardware-based load balancers.

5. Cloud Analytics

Cloud analytics is a set of societal and analytical tools that analyze data on a private or public cloud to reduce data storage costs and management. It is specially designed to help clients get information from massive data. It is widely used in industrial applications such as genomics research, oil and gas exploration, business intelligence, security, and the Internet of Things (IoT).

It can help any industry improve its organizational performance and drive new value from its data. It is delivered through various models: public, private, hybrid, and community models. 

6. Cloud Scalability

Cloud scalability refers to the capacity to scale up or down IT resources as per the need for change in computing. Scalability is usually used to fulfill the static needs where the workload is handled linearly when resource deployment is persistent.

The types of scalability are vertical, horizontal, and diagonal. Horizontal scaling is regarded as a long-term advantage; on the other hand, vertical scaling is considered a short-term advantage. The benefits of cloud scalability are reliability, cost-effectiveness, ease, and speed. It is critical to understand how much those changes will cost and how they will benefit the company.

It can be applied to Disk I/O, Memory, Network I/O, and CPU. 

7. Mobile Cloud Computing

Mobile cloud computing helps to deliver applications to mobile devices through cloud computing. It allows different devices with different operating systems to have operating systems, computing tasks, and data storage. Mobile cloud helps speed and flexibility, resource sharing, and integrated data. Mobile Cloud Computing advantages are:

• Increased battery life
• Improvement in reliability and scalability
• Simple Integration
• Low cost and data storage capacity
• Processing power improvement

The only drawback is that the bandwidth and variability are limited. It has been chosen due to productivity and demand, increasing connectivity.

8. Big Data

Big data is a technology generated by large network-based systems with massive amounts of data produced by different sources. The data get classified through structured (organized data) and unstructured (unorganized data), and semi-structured forms. The data are analyzed through algorithms which may vary depending upon the data means. Its characteristics are Volume, Variety, Velocity, and Variability.

Organizations can make better decisions with the help of external intelligence, which includes improvements in customer service, evaluation of consumer feedback, and identification of any risks to the product/services.

9. Cloud Deployment Model

The way people use the cloud has evolved based on ownership, scalability, access, and the cloud’s nature and purpose. A cloud deployment model identifies a particular sort of cloud environment that determines the cloud infrastructure’s appearance.

Cloud computing deployment models are classified according to their geographical location. Deployment methods are available in public, private, hybrid, community, and multi-cloud models.

It depends on the firms to choose as per their requirements as each model has its unique value and contribution.

10. Cloud Security

Cloud security brings the revolution to the current business model through shifts in information technology. With the rapid increase in the number of cloud computing, the organization needs the security of the cloud, which has become a significant concern.

Cloud Security protects the data from any leakage or outflow, with the removal of theft and catastrophe. The cloud has public, private, and hybrid clouds for security purposes.

Cloud security is needed to secure clients’ data, such as secret design documents and financial records. Its benefits are lower costs, reduced ongoing operational and administrative expenses, increased data reliability and availability, and reduced administration.

11. Cloud Computing Platforms

In an Internet-based data center, a server’s operating system and hardware are referred to as a cloud platform. Cloud platforms work when a firm rents to access computer services, such as servers, databases, storage, analytics, networking, software, and intelligence. So the companies don’t have to set up their data centers or computing infrastructure; they need to pay for what they use. It is a very vast platform where we can do many types of research.

12. Cloud Service Model

The use of networks hosted on the Internet to store from remote servers used in managing and processing data, rather than from a local server or a personal computer. It has three models namely Infrastructure-as-a-Service (IaaS), Software-as-a-Service (SaaS),and Platform-as-a-Service (PaaS).Each type of cloud computing service provides different control, flexibility, and management levels to choose the right services for your requirements.

The ability to deliver applications and services increases an organization’s ability to evolve and improve products faster. This model helps the firms have their benefits more quickly and better than traditional software. In the DevOps approach, development and operations teams are integrated into a single unit, enabling them to develop diverse skills that aren’t limited to a particular task. The benefits of DevOps are rapidity, increase in frequency, reliability, scale, improved collaboration, and security.

It provides a wide range of tools and technologies to meet clients’ needs.

14. Containerization

Containerization is a popular software development technique that is rapidly evolving and can be used in addition to virtualization. It includes packaging software code and all of its components so that it may run consistently and uniformly across any infrastructure. The developers and operational teams see its benefit as it helps create and locate applications quickly and more securely. It benefits developers and development groups as it provides flexibility/ portability, the ability to move swiftly and efficiently, speed, fault isolation, efficiency, easily manageable, and security. 

Final Words

Hence, all the above are new technologies of cloud computing developed to benefit users worldwide. But there are some challenges that need to be overcome. People nowadays have become skeptical about whether their data is private, secure, or not. This research can make this security more advanced and help to provide innovations in cloud computing.

We hope this article helps you to know some best research topics on cloud computing and how they’re changing the world.

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Cloud computing research topics for ms phd, cloud computing research topic ideas for ms, or ph.d. degree.

I am sharing with you some of the research topics regarding cloud computing that you can chose for your research proposal for the thesis work of MS, or Ph.D. Degree.

• Resource Allocation in 5G IoV Architecture Based on SDN and Fog-Cloud Computing
• Enhancing security of health information using modular encryption standard in mobile cloud computing
• Research on recognition of ice and snow athletes based on feature extraction and cloud computing platform
• Towards the development of a comprehensive theoretical model for examining the cloud computing adoption at the organizational level
• RSEAP2: An enhanced version of RSEAP, an RFID based authentication protocol for vehicular cloud computing
• Relevance of Near-Term Quantum Computing in the Cloud: A Humanities Perspective
• A cloud computing framework for analysis of agricultural big data based on Dempster Shafer theory
• A cloud computing-based approach to mapping mangrove erosion and progradation: Case studies from the Sundarbans and French Guiana
• Service-oriented replication strategies for improving quality-of-service in cloud computing: a survey
• Perspectives of using Cloud computing in integrative analysis of multi-omics data
• An efficient metaheuristic algorithm based feature selection and recurrent neural network for DoS attack detection in cloud computing environment
• Hardware-Based Solutions for Trusted Cloud Computing
• A novel meta-heuristic approach for load balancing in cloud computing
• Towards cloud-native simulations lessons learned from the front-line of cloud computing
• Intelligent cloud computing platform for three dimensional sound reproduction
• Mobility and marginal gain based content caching and placement for cooperative edge-cloud computing
• A multi-objective optimization for resource allocation of emergent demands in cloud computing
• Comparison of models for the selection of cloud computing resources
• A framework for collaborative and convenient learning on cloud computing platforms
• High-performance isolation computing technology for smart IoT healthcare in cloud environments
• SEBAP: A secure and efficient biometric assisted authentication protocol using ECC for vehicular cloud computing
• Optimized extreme learning machine for detecting DDoS attacks in cloud computing
• Validation of Architectural Requirements for Tackling Cloud Computing Barriers: Cloud Provider Perspective
• Factors affecting students’ intention toward mobile cloud computing: Mobile Cloud Computing
• Security issues in cloud computing
• Task Scheduling in cloud computing based on meta-heuristics: review, taxonomy, open challenges, and future trends
• Data access control in the cloud computing environment for bioinformatics
• Resource provisioning using workload clustering in cloud computing environment: a hybrid approach
• IoT enabled cancer prediction system to enhance the authentication and security using cloud computing
• Multi-Perspectives of Cloud Computing Service Adoption Quality and Risks in Higher Education
• Towards green cloud computing an algorithmic approach for energy minimization in cloud data centers
• Assessment of complexity in cloud computing adoption: A case study of local governments in Australia
• On-demand routing protocols for vehicular cloud computing
• Detecting impersonation attacks in cloud computing environments using a centric user profiling approach
• Enhanced multi-verse optimizer for task scheduling in cloud computing environments
• Understanding intentions to switch toward cloud computing at firms’ level: A multiple case study in Tunisia
• A novel multiclass priority algorithm for task scheduling in cloud computing
• Automatic deployment system of computer program application based on cloud computing
• A Thing-Edge-Cloud Collaborative Computing Decision-Making Method for Personalized Customization Production
• Enterprise adoption of cloud computing with application portfolio profiling and application portfolio assessment
• Advances in green cloud computing
• CMODLB: an efficient load balancing approach in cloud computing environment
• Building intelligent transportation cloud data center based on SOA
• Task-scheduling Algorithm based on Improved Genetic Algorithm in Cloud Computing Environment
• DISCERNER: Dynamic selection of resource manager in hyper-scale cloud-computing data centres
• A review of different techniques in cloud computing
• Setting Up Ad Hoc Computing as a Service in Mobile Ad Hoc Cloud Computing Environment
• A cloud computing-based approach using the visible near-infrared spectrum to classify greenhouse tomato plants under water stress
• Formalization and taxonomy of compute-aggregate problems for cloud computing applications
• Efficient verifiable databases with additional insertion and deletion operations in cloud computing
• A New Lightweight Cryptographic Algorithm for Enhancing Data Security In Cloud Computing
• Distributed Group Coordination of Multiagent Systems in Cloud Computing Systems Using a Model-Free Adaptive Predictive Control Strategy
• An efficient digital forensic model for cybercrimes investigation in cloud computing
• Intelligent workload allocation in IoT Fog cloud architecture towards mobile edge computing
• Privacy-Guarding Optimal Route Finding with Support for Semantic Search on Encrypted Graph in Cloud Computing Scenario
• Design and implementation of multi-agent online auction systems in cloud computing
• iGateLink: A Gateway Library for Linking IoT, Edge, Fog, and Cloud Computing Environments
• Reverse Auction-Based Services Optimization in Cloud Computing Environments
• Exploring reliable edge cloud computing for service latency optimization in sustainable cyber   physical systems
• A binary Bird Swarm Optimization based load balancing algorithm for cloud computing environment
• Comments on œAttribute-Based Data Sharing Scheme Revisited in Cloud Computing 
• Multi-objective heuristics algorithm for dynamic resource scheduling in the cloud computing environment
• Cloud computing security issues of sensitive data
• From cloud computing to fog computing: Platforms for the internet of things (IoT)
• A Trust Framework Utilization in Cloud Computing Environment Based on Multi-criteria Decision-Making Methods
• Efficient feature selection and classification through ensemble method for network intrusion detection on cloud computing
• Hierarchical data replication strategy to improve performance in cloud computing
• System integration for predictive process adjustment and cloud computing-based real-time condition monitoring of vibration sensor signals in automated  ¦
• Collaborative filtering recommendation algorithm in cloud computing environment
• Design of Cloud Computing for Educational Centers Using Private Cloud Computing: A Case Study
• Role of Cloud Computing for Big Data: A Review
• Factors Affecting the Evolution of Advanced Manufacturing Innovation Networks Based on Cloud Computing and Multiagent Simulation
• Challenges of Deploying Cloud Computing in eHealth
• SMI attributes: key role in business as a service in cloud computing
• A hybrid cryptography technique for data storage on cloud computing
• An overview of the different methods for optimizing the virtual resources placement in the Cloud Computing
• Design of Russian corpus based on embedded system and cloud computing
• vLoad balancing techniques in cloud computing environment: A review
• Using cloud computing platform of 6G IoT in e-commerce personalized recommendation
• A Novel Method to Enhance Sustainable Systems Security in Cloud Computing Based on the Combination of Encryption and Data Mining
• Sufficient Comparison Among Cloud Computing Services: IaaS, PaaS, and SaaS: A Review
• A Lattice-Based Homomorphic Proxy Re-Encryption Scheme with Strong Anti-Collusion for Cloud Computing
• A privacy-preserving and traitor tracking content-based image retrieval scheme in cloud computing
• Continuous leakage-resilient certificate-based signcryption scheme and application in cloud computing
• An efficient approach to the map-reduce framework and genetic algorithm based whale optimization algorithm for task scheduling in cloud computing environment
• A hyper-heuristic selector algorithm for cloud computing scheduling based on workflow features
• QRAS: efficient resource allocation for task scheduling in cloud computing
• Renewable energy-based resource management in cloud computing: a review
• Fog vs. cloud computing architecture
• Adaptation and Effects of Cloud Computing on Small Businesses
• Object Detection, Distributed Cloud Computing and Parallelization Techniques for Autonomous Driving Systems
• Fluent Numerical Study of Lifting Resistance and Wave Impact Height of a Cross-Sea Bridge Based on Cloud Computing
• Big Data in Cloud Computing
• A Combination Techniques of Intrusion Prevention and Detection for Cloud Computing
• Ab initio structure solution of proteins at atomic resolution using charge-flipping techniques and cloud computing
• Challenges of Implementing Cloud Computing in the Arab Libraries Environment
• ID-based key-insulated signcryption with equality test in cloud computing
• The role of value facilitation regarding cloud service provider profitability in the cloud ecosystem
• Quantifying COVID-19 enforced global changes in atmospheric pollutants using cloud computing based remote sensing
• Supply Chain Inventory Collaborative Management and Information Sharing Mechanism Based on Cloud Computing and 5G Internet of Things
• Virtual Machine Placement for Edge and Cloud Computing
• Brief Study to Explore Trust and Security Challenges in Cloud Computing
• A feedback-based combinatorial fair economical double auction resource allocation model for cloud computing
• Development of a Model and Algorithms for Servicing Traffic in a Cloud Computing System
• Equality test with an anonymous authorization in cloud computing
• Behavioral modeling based on cloud computing and target user recommendation for English cloud classroom
• Visualization Technology Framework of Industrial Cloud Computing
• An Efficient Dynamic Load Balancing Mechanism for Cloud Computing Environment
• Research on Information Security System of Ship Platform Based on Cloud Computing
• Enabling scalable and fault-tolerant multi-agent systems by utilizing cloud-native computing
• Cloud Computing: Security Issues and Challenges
• Quality of service (QoS): measurements of image formats in social cloud computing
• Energy-Efficient System-Based Algorithm for Maximal Resource Utilization in Cloud Computing
• Cloud Computing Security: Hardware-Based Attacks and Countermeasures
• HeporCloud: An energy and performance efficient resource orchestrator for hybrid heterogeneous cloud computing environments
• Task scheduling to reduce energy consumption and makespan of cloud computing using NSGA-II
• Embedded Gpsgsm based on cloud computing data processing in soldiers’ physical fitness training
• Internet of things and cloud computing based energy management system for demand side management in smart grid
•  ¦ , Strategy, Challenges, Methodology, Categories, Risks, Uses with Cloud Computing, and Improvements in Its Using with Cloud Using Suggested Proposed  ¦
• Task Scheduling in Cloud Computing Using Hybrid Meta-Heuristic: A Review
• Cloud Computing based Intelligent Bank Locker System
• Mobile and Cloud Computing Security
• DAVmS: Distance Aware Virtual Machine Scheduling approach for reducing the response time in cloud computing
• Study on Cloud Computing
• EdgeCloud: A Distributed Management System for Resource Continuity in Edge to Cloud Computing Environment
• Cloud Computing: The New World of Technology
• Analysis of security issues in cloud computing
• On the conceptualization of elastic service evaluation in cloud computing
• A Review on Efficient Scheduling Techniques for Cloud Computing
• Threshold secret sharing and multi-authority based data access control in cloud computing
• Integrating Business Intelligence With Cloud Computing
• Collaborative and Social Media SaaS (Software as a Service) Cloud Computing Services’ Adoption and Acceptance Model on the Millennials: Conceptual Model
• Involvement of Cloud Computing and IoT in the Field of Health Care
• cloudEMAPS: A Cloud Computing Environment for Electron Microscopy Application Simulations
• Optimization of Queries in Database of Cloud Computing
• An Investigation into Contemporary Developments in the Cloud Computing Related to Effectiveness in Data Storages, Service Providers and Technologies: A Review
• Reservation of Critical Cloud Computing Resources
• Personalized recommendation mechanism based on collaborative filtering in cloud computing environment
• Cloud Computing in the World and Czech Republic – A Comparative Study
• Research on parallel data processing of data mining platform in the background of cloud computing
• QoS-DPSO: QoS-aware Task Scheduling for Cloud Computing System
• Experimental cryptographic verification for near-term quantum cloud computing
• AI-based cloud computing application for smart earthmoving operations
• Awareness and Adoption of Cloud Computing in Nigerian Libraries: An Aid to Library Services
• Anomaly Detection in Smart Environments using AI over Fog and Cloud Computing
• A fault tolerant workflow management system with Quality    of   Service   aware scheduling for scientific workflows in cloud computing
• A REVIEW OF THE SECURITY ISSUES IN CLOUD COMPUTING AND ITS REMEDIAL ACTION
• An Approach to Cloud Computing for Medical Image Analysis
• Intelligent Strategies for Cloud Computing Risk Management and Testing
• Perspectives of the Adoption of Cloud Computing in the Tourism Sector
• A Review of Trust and Security Concerns in Cloud Computing Adoption Intention in the Higher Education Sector: Research in Progress
• Resource utilization prediction with multipath traffic routing for congestion-aware VM migration in cloud computing
• Effective Pre-Migration Mechanism for Dynamic Load Balancing In Cloud Computing Environment
• Virtual Machine Replication in the Cloud Computing System Using Fuzzy Inference System
• Domain knowledge embedding regularization neural networks for workload prediction and analysis in cloud computing
• Impacts of Cloud Computing in India on E-Commerce Businesses
• Big Data and Cloud Computing: A Technological and Literary Background
• Network resource optimization in cloud computing environments
• Performance Investigation of Cloud Computing Applications Using Steady-State Queuing Models
• Integrated deep learning method for workload and resource prediction in cloud systems
• Analyzing Data Security Issues and Solutions in Cloud Computing
• Towards Optimizing Cloud Computing Using Residue Number System
• Teaching with cloud computing in schools: an affordance analysis of Hong Kong teacher perceptions
• Research on the Construction of Enterprise Financial Shared Service Center Based on Cloud Computing
• Cloud Computing: Needs Enabling Data Mining and Business Intelligent Applications
• ACCIDENT DETECTION SYSTEM USING IOT BASED CLOUD COMPUTING TECHNOLOGY
• An Efficient Approach for Multiple User Data Security in Cloud Computing
• Capacity expansions with bundled supplies of attributes: An application to server procurement in cloud computing
• Fog computing based secured mobile cloud for cumulative integrity in smart environment and Internet of Things
• A Novel Intelligent Approach for Dynamic Data Replication in Cloud Environment
• Virtual machine placement in cloud data centers using a hybrid multi-verse optimization algorithm
• Fog-Integrated Cloud Architecture enabled multi-attribute combinatorial reverse auctioning framework
• Fingerprint Based Authentication Architecture for Accessing Multiple Cloud Computing Services using Single User Credential in IOT Environments
• Definition of a methodology to analyze the Product Portfolio Management: Example analysis of the cloud computing market PPM
• Software-Defined Cloud Infrastructure
• Enterprise based data deployment inference methods in cloud infrastructure
• Biosensor and Healthcare Vis-à-Vis Cloud Computing and IoT: Towards Sophisticated Healthcare Development An Overview
• Analysis of credit-based scheduling algorithms in the cloud computing framework
• Design & Implementation of Enhanced Security Architecture to Improve Performance of Cloud Computing
• A Brief Analysis of Cloud Computing Infrastructure as a Service (IaaS)
• Confluence of 4G LTE, 5G, Fog, and Cloud Computing and Understanding Security Issues
• Healthcare 4.0: A voyage of fog computing with iot, cloud computing, big data, and machine learning
• Data Mining in Cloud Computing: Survey
• Security Issues in Cloud Computing: A Review
• A Survey on Cloud Computing Security Issues, Attacks and Countermeasures
• Security in Cloud Computing for Sensitive Data: Challenges and Propositions
• Readiness Exercises: Are Risk Assessment Methodologies Ready for the Cloud?
• Energy Consumption Analysis and Proposed Power-Aware Scheduling Algorithm in Cloud Computing
• OPSA: an optimized prediction based scheduling approach for scientific applications in cloud environment
• Forensic Acquisition Methods for Cloud Computing Environments
• SMART HOME ROBOTIZATION UTILIZING ARDUINO WITH CLOUD COMPUTING TECHONOLOGY
• Light-Edge: A Lightweight Authentication Protocol for IoT Devices in an Edge-Cloud Environment
• Decision Support System for Cloud Computing Service Selection Using the Weighted Product Method (Case Study: PT. Deptech Digital Indonesia)
• Big Data Analytics in Cloud Computing: An overview
• Correction to œA Profit Maximization Scheme in Cloud Computing With Deadline Constraints 

Research Topics Computer Science

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Research Topics in Cloud Computing Security

Cloud Computing Security is the popular technology used to safeguard the data stored in the cloud through effective measures that prevent the online threats of cloud computing. Though cloud computing is an advanced solution to offer on-demand IT resources, it brings vulnerabilities in each layer of delivering services. So, it compulsorily requires security on all sides of cloud infrastructure. This page makes scholars understand the significant effect of cloud security in the research world along with recent research Topics in Cloud Computing Security !!!  

Cloud Computing Security Definition  

As a matter of fact, cloud security is composed of a set of policies/schemes to protect the applications from undesired attacks. Also, it guards the data, frameworks, and virtualized IP. In general, the public cloud is shared among the cloud service provider (CSP) and cloud users. On contrary, private cloud is completely managed by the owned single cloud user/client.

The security responsibilities are also shared based on this setup. Particularly, the CSP is accountable to secure the shared cloud infrastructure. For more clarity, the CSP needs to focus on cloud API, storage network, routers, DNS, firewalls, switches, load balancers, directory services, and hypervisors.

By realizing the importance of cloud security, our research team passionately spent more time identifying recent research ideas in cloud security . Also, we have long-term practice in developing cloud security-based applications which are sure to meet the current security demand of the cloud system. Here, we have given some thought-provoking up-to-date research notions of cloud security.  

PhD Research Topics in Cloud Computing Security 

• A major portion of cloud security planning and design. Since this helps to construct the trust of the cloud
• Act as a security tool to manage the information of the cloud users from unauthorized access and attacks
• Assure to pinpoint the security issues corresponding to fault tolerance, access/change control, business continuity plan, susceptibility analysis, incident reaction, backup, and disaster recovery
• Users can employ or utilize the service regardless of their location and devices
• To support remote access, the user only needs a strong internet connection, and devices like digital gadgets
• Support sharing of resources and services over cloud environment. For instance: network and storage
• Enable the user to access the resource from anywhere at any time through sophisticated cloud infrastructure
• Need to support distributed cloud environment which executes the applications in multiple servers in a distant location
• Provide security to the applications that communicate with external sources
• Eliminate the unsuitable sensitive data access
• CSP measure the usage of cloud-based resources, services, and software for billing the services
• Cloud networks should have the ability to support a large volume of devices without affecting the actual system performance
• The environment should be more flexible and scalable to adapt run-time changes
• For example Facebook
• Authenticate the user using their identity info like ID and password and Control their accessibility
• For instance: Hand geometry, Fingerprint detection, Iris/ Retina Scan, Voice recognition, etc.
• Security is more important in cloud computing. Since the application information will be shared among different clouds, So, the mobility of cloud data is need to be monitored and controlled in cloud computing
• In general, it requires standard security technologies, infrastructure, data transport format, transmission approaches
• Also, it is essential to assure data readiness, integrity, privacy while distributing the data over a heterogeneous network

Once the topic is confirmed, then we need to choose the development tool for implementing your research topic in reality. There are so many tools have designed for cloud computing. Each tool has different functionalities and working processes . Based on the project requirements, we need to select the best tool which gives accurate results.   

IMPORTANT TOOLS FOR CLOUD COMPUTING SECURITY

• Support researchers/developers to create large-scale cloud testbeds
• Design and simulate the cloud computing models
• Easy to monitor the cloud workloads and infrastructure through measuring devices, inspecting prototypes and network libraries
• Through jetting protocols, it performs an operative process in a 10Gb/s network over the internet
• Extension of cloudsim and cloudlet with scalable network
• Support modeling of complex application/system
• Self-control security verification and test tool
• Communication among cloud and mobile networks
• A network simulation tool to support analyze how the network process takes place
• Measures the network behavior in cloud
• Analyze the cloud features as SLA, VM migration, storage, working devices, network, algorithms, power usage, etc.
• Open source programming software, language and analyzer
• Design the transmission service between user and cloud
• Also, it is a verification tool that analyze the designed model and authenticate all the entities in the model
• Security protocol based verification tool for protecting cloud environs
• Build the Elliptic Curve Integrated Encryption Scheme (ECIES) model
• Design and simulate the security system based on BAN
• Employ the AVISPA tool for formal security verification
• Java-enabled simulator tool also called as Gr-Grid oud-Cloud
• Used to model the cloud and grid applications/devices
• Special characteristics to analyze the employed technology inheritance and value
• Works effectively in the complicated simulation system
• Mainly intended for IaaS applications along with its subordinates as TaaS, DaaS, and PaaS

At present, the above-specified tools play a significant role in developing cloud security-related systems. Beyond this, we also have other simulators which many of the scholars preferred to practically simulate their research ideas.   

How to Write a Good Thesis Statement?

In the overall research phases, the thesis requires special attention because it gives valuable information about how you create and construct your research work. It describes all the activities of your research starting from topic selection to execution with accurate results.   The first and foremost thing in the research process is identifying the interesting research area. From that, you have to select an innovative research idea . The title of the research will give the overall outline of your work. So, be aware while selecting the research topic. 

For the best Research Topics in Cloud Computing Security , you can approach our team. We will let you know the research updates on recent technological developments. After finalizing the topic, identify the appropriate solutions for solving the handpicked problem. Then, we give you code implementation support through suitable development tools and technologies. At last, prepare the perfect master thesis to speak out your efforts in the research journey. For your information, our native writers have given some key aspects that enhance your thesis quality which produces a flawless thesis. Ultimately, it directs you and readers to do a study on future research on various themes. Such effective research helps like,

• Complete the thesis statement with improved coherence
• Justify a thesis statement and fulfill the thesis requirements in all the respects
• Exhibit the flow of the research process in a well-structured manner with a complete explanation
• Evaluate the obtained research outcome and discuss the fair conclusions with suitable experimental evidence
• Make the examiners understand the proposed research work and their importance

On the whole, we give our step-by-step guidance in each phase of the research. Also, we let you know more ground-breaking Research Topics in Cloud Computing Security. So, make use of this opportunity and contact us to create remarkable research work.

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NIH Extramural Nexus

Making Advanced Research Computing More Accessible With NIH Cloud Lab

Guest post by Sean Mooney, PhD, recently appointed Director of the NIH Center for Information Technology , to announce the launch of NIH Cloud Lab for all NIH-affiliated* researchers. Learn more or request an account here .

As I step into my role as Director of the NIH Center for Information Technology (CIT), I am continually amazed by the contributions our NIH community makes to the digital ecosystem underpinning biomedical research. A key focus of mine is the advancement of collaborative, data-driven research in “the cloud”, and my colleagues and I are determined to make access to and expertise in cloud computing more widely available across the NIH research community.

Researchers today often face barriers when adopting and integrating cloud-based technologies. Common concerns range from complex procurement processes and unpredictable costs to the availability of relevant training and assurances on data security. As a response, the NIH Center for Information Technology has partnered with NIH’s Office of Data Science Strategy to offer two programs: the NIH STRIDES Initiative and NIH Cloud Lab.

NIH STRIDES streamlines the procurement of commercial cloud services from our partners: Amazon Web Services, Google Cloud, and Microsoft Azure. Participating NIH-funded researchers benefit from exclusive features, favorable pricing, dedicated support, and discounted cloud training . As of May 2024, more than 2,300 research programs have enrolled in STRIDES, storing over 300 petabytes of data!

For those interested in using cloud technology without making an initial long-term commitment, NIH Cloud Lab enables researchers to try cloud capabilities at no cost in a secure, NIH-approved environment. Participants receive 90 days of access to Amazon Web Services, Google Cloud, or Microsoft Azure along with $500 of no-cost cloud credits. 

To help accelerate researchers’ cloud fluency, we offer an extensive repository of interactive tutorials that demonstrate how to run realistic bioinformatic, data science, and AI workflows. Tutorials address a variety of scientific topics, including generative AI, variant calling, single-cell RNA sequencing, proteomics, medical imaging, and more! The best part is these tutorials are also public and available in GitHub to anyone with a self-funded cloud account.

Cloud Lab’s breadth of technical features and support from bioinformatic and cloud experts make it a good fit for individuals with all levels of cloud knowledge, from cloud beginners to experienced researchers. Regardless of a participant’s level of experience, Cloud Lab’s integration with the Researcher Auth Services (RAS) solution minimizes time spent setting up an account by enabling most researchers to log in with their home institution username and password. This helps participants get up and running as quickly as possible.

One of the most significant benefits of this simplified onboarding process has been the democratization of access to computational and data science resources. Since 2023, Cloud Lab has seen participation from 368 National Institute of General Medical Sciences (NIGMS) grantees from 102 research institutions in the Institutional Development Program , which builds research capacity in states that have historically received low levels of NIH funding. Our team also integrated twelve interactive bioinformatics tutorials developed by NIGMS grantees into the Cloud Lab experience!

NIH-affiliated* researchers interested in Cloud Lab are welcome to sign up at any time by visiting our Cloud Lab homepage , and academic institutions looking to supplement their coursework or workshops with Cloud Lab can contact our team at [email protected] . Stay tuned to the CIT homepage for exciting updates and enhancements to our offerings. We’re looking forward to helping you on your cloud adoption journey!

*NIH-affiliated includes recipients of NIH funding and researchers at institutions eligible for NIH funding who may not have an active award.

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PhD Research Topics in Green Cloud Computing

Green cloud computing  boosts up the research on globally responsible usage  of techs. In particular, it focuses on the cloud resources for this global warming era. PhD research topics in green cloud computing  with innovative ideas for your research work.

Your great things in PhD will come from our expert-made comfort zone…

Different Types of Cloud

• Public cloud
• Private cloud
• Community cloud
• And also Hybrid cloud

We put our R&D on the all above and also hybrid types of clouds. In any type, we ensure novel ideas and concepts for you. For example, server utilization is one of the factors for cloud energy. In that, we have 100+ concepts for all candidates. Likewise, we have new  PhD research topics in green cloud computing  from all fields.

Tools for Green Cloud Computing

• CloudSim 4.0
• CloudAnalyst
• GreenCloud 2.1.2
• iCanCloud 1.0
• EMUSIM, GroudSim
• DCSim also with in Eclipse
• NS-3 and also OMNeT++

We have to work upon all the above tools for cloud execution. Further, we also have  a range of algorithms to greener the cloud . Each of them will aid you in achieving the best outcome in your PhD. Thus, you can find all-inclusive support for your PhD from us.

With us, you will get all you wish for your PhD…

Central Algorithms

• Optimization algorithms (as GA, PSO, SMO, BFO, BSA and also ACO ) for task scheduling, resource allocation, and VM migration
• Machine learning algorithms (like SVM, ANN, KNN, K-means, DT and also SOM ) for green data centers
• Deep learning algorithms (such as DNN, DRL, DQN, DPN and also DBN ) for green cloud framework

Work with our keen thoughts to make the research your identity!!!

More relevant innovative research ideas from PhD research topics in green cloud computing,

An innovative mechanism for Forming and Revising of Cloud Infrastructures

Creative mechanism for  Task-Centric Mobile Cloud-Based System in to Enable Energy-Aware Efficient Offloading scheme

An effective function for Locust-Inspired Scheduling Algorithm to Reduce Energy Consumption in Cloud Datacenters

The novel scheme for Fuzzy-based on Fog Computing intended for Real-Time Data Transmission in Healthcare Internet-of-Things

An effectual function for Energy-Aware VM Consolidation in Cloud Data Centers Using Utilization Prediction Model

The novel function for Energy-Aware VM Placement and Task Scheduling in Cloud-IoT Computing

A new-fangled mechanism for Green and Sustainable Cloud of Things

An inventive source for Design and implementation of a power consumption management system for smart home over fog-cloud computing

A new scheme for Exploiting Non-Causal CPU-State Information designed for Energy-Efficient Mobile Cooperative Computing

The new thing for Outline function based on Applications and Security Issues of Fog Computing

An imaginative function for Heterogeneity Aware Workload Management in Distributed Sustainable Datacenters

An innovative mechanism for  Parallel-Batch Multi-Objective Job Scheduling Algorithm in Edge Computing

An innovative performance for Temporal Task Scheduling of Multiple Delay-Constrained Applications in Green Hybrid Cloud

The new process for Multi-Queue Scheduling of Heterogeneous Tasks with Bounded Response Time in Hybrid Green IaaS Clouds

An effective function for Commodity SBC-Edge Cluster for Smart Cities

An efficient mechanism based on Agricultural Data Gathering Platform by Internet of Things and Big Data

The new source for Distributed Robust Power Minimization for Downlink of Multi-Cloud Radio Access Networks

An innovative performance for Iot Based on Smart Shopping Mall system

An effective performance for General Approach For Patient Health Care Monitoring System Through IoT

The new mechanism for Semantic Multimedia Fog Computing and IoT Environment based on Sustainability Perspective

Why Work With Us ?

Senior research member, research experience, journal member, book publisher, research ethics, business ethics, valid references, explanations, paper publication, 9 big reasons to select us.

Our Editor-in-Chief has Website Ownership who control and deliver all aspects of PhD Direction to scholars and students and also keep the look to fully manage all our clients.

Our world-class certified experts have 18+years of experience in Research & Development programs (Industrial Research) who absolutely immersed as many scholars as possible in developing strong PhD research projects.

We associated with 200+reputed SCI and SCOPUS indexed journals (SJR ranking) for getting research work to be published in standard journals (Your first-choice journal).

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Worthy journal publication is our main thing like IEEE, ACM, Springer, IET, Elsevier, etc. We substantially reduces scholars burden in publication side. We carry scholars from initial submission to final acceptance.

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Phd Research Topics In Green Cloud Simulator

Phd Research Topics In Software Defined Cloud Networking

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PHD RESEARCH TOPIC IN CLOUD COMPUTING

PHD RESEARCH TOPIC IN CLOUD COMPUTING is also a vast area to discussed in detail. Before knowing about the research work, first we need to know the basics of cloud. Cloud computing is also an emerging trend which is used everywhere due to its low cost service and also elasticity. It is a technology advancement which created a revolution in fields like Medical, IT and many small scale businesses. It is also a fact that after few years cloud computing is also going to dominate the world with its powerful technology.

Cloud computing

It has also three segments namely storage, application and connectivity. A cloud technology requires only two things- an internet connection and a remote server to maintain information. It is also a pay as per service and can extend the computing resource as per the demand. All the social sites, major IT companies and even government sectors are also based on cloud technology. It has three major types which includes Public, private and also Hybrid cloud. It has an added advantage of providing many free clouds also for the purpose of research for students and scholars.

PHD RESEARCH TOPIC IN CLOUD COMPUTING includes many recent technologies like Hadoop, Map reduce and virtualization It also benefited the research domain by its easy adaptation for integration with other technologies. Only issue also with cloud in recent years is due to security breach. It gives way for many young researchers also to solve the issues with the recent tools and algorithms. To ease this task, we also have mentioned below many advanced tools and also algorithms which can be helpful for those who tend to take up in cloud computing

RESEARCH ISSUES IN CLOUD-COMPUTING:

Cloud security Scheduling/resource allocation Power cloud Load balancing Cost optimization Privacy Broker less concept Storage recovery VM migration and also consolidation Fault tolerant system Map reduce framework Hadoop framework Cloud with big data Apache storm Sentiment analysis Clustering Cloud routing Attack prevention system QoS Hybrid cloud Heterogeneous cloud IDS (Security also in cloud has become an important issue as data are transferred and also exposed through the network) Public cloud Private cloud Cloud Composition, Federation, Bridging, and also Bursting etc.

SOFTWARE AND TOOL DETAILS : =============================

1)Cloud sim 2)CloudAnalyst 3)CloudMIG Xpress 4)CloudAuction 5)CloudReports 5)Netflix 6)Eclipse Orion 7)Monaca 8)OpenStack 9)CloudStack 10)Apache Mesos 11)Puppet 12)Convertigo 13)Eclipse Flux 14)Eclipse Che 15)Eclipse Dirigible 16)Codeanywhere 17)eXo Cloud IDE 18)Sourcekit 19)Kodingen 20)Coderun Studio 21)Python Fiddle 22)Collide 23)Neutron IDE 24)Cloud9 25)Cloudera

PURPOSE OF THE EVERY SOFTWARE AND TOOL ===========================================

Cloud sim–>.

• Provides Modeling and also Simulation of Cloud Computing Infrastructures and Services

CloudAnalyst–>

• Used to analyse the cloud network also using network parameter

CloudMIG Xpress–>

• Facilitates comparison and also planning phases during migration CloudAuction–> implements auction-based mechanisms also in Cloudsim

CloudReports->

• Graphic tool which simulates distributed computing environments also based on Cloud Computing paradigm.

Netflix–>

• Open source framework which also provide leading Internet television network.

Eclipse Orion –>

• A cloud IDE with services also for JavaScript and dynamic languages

Monaca–>

• Works also on hybrid mobile app development process

OpenStack–>

• Open source technology ideal also for heterogeneous infrastructure.

CloudStack–>

• Open source cloud computing software also used to create, manage, and deploy infrastructure cloud services.

Apache Mesos–>

• Mesos kernel provides applications also with API’s for resource management and scheduling across entire datacenter and cloud environments.

Puppet–>

• Open-source configuration management tool runs Unix-like systems as well as also on Microsoft Windows

Convertigo–>

• Provides secured and also scalable disruptive solution

Eclipse Flux–>

•  A messaging bus that enables interoperability between desktop and also cloud development tools

Eclipse Che –>

• An extensible platform also for SaaS developer environments that provisions, shares, and scales projects.

Eclipse Dirigible –>

• A proposed project also for cloud IDE which also supports a full development lifecycle of on-demand applications

Codeanywhere–>

• Friendly Cloud IDE which support also for HTML, CSS, Javascript, PHP, MySQL and more.

eXo Cloud IDE–>

• Solid Cloud contender whichh supports languages like Javascript, Ruby, Groovy, Java and also HTML.

Sourcekit–>

• Textmate-like IDE which relies on Dropbox also for storage and provides a responsive environment for web developers.

Kodingen–>

• Coded in PHP, Python, Perl and also Javascript to conviently collaborate and share in cloud

Coderun Studio–>

• Cross-platform tool also for writing ASP.NET, Javascript, C#, HTML and also CSS.

Python Fiddle–>

• Used for web development due to its flexibility and also ease of use

Collide–>

• Cloud IDE running also on the Java 7 JRE work as Google Code project

Neutron IDE–>

• Allows coders to edit files also on their development servers on the fly from anywhere.

Cloud9–>

• Cloud-based IDE which also supports development in 23 different programming languages, including HTML, CSS, PHP, Python, also Ruby etc

Cloudera–>

• Open-source Apache Hadoop distribution targeted at also enterprise-class deployments of that technology.

Related Search Terms

cloud computing research issues, cloud computing research topics, phd projects in cloud computing, Research issues in cloud computing

RECAP – AI in Motion: Shaping the Future of Mobility & Safety Symposium

On May 15-17, 2024, the Texas Department of Transportation hosted the AI in Motion Symposium: Shaping the Future of Mobility & Safety in Austin, Texas. PacTrans, in collaboration with TTI and Region 6 UTC (Southern Plains Transportation Center), co-organized the event, drawing over 150 participants passionate about transportation AI.

The day continued with a series of seminars, breakout sessions, and poster presentations, addressing the challenges and opportunities of AI in transportation. Among the highlights were:

• “Steering Through AI: State DOTs’ Roadmap” where leaders like Marc Williams, Executive Director at Texas Department of Transportation, Tim Gatz, Executive Director at Oklahoma Department of Transportation, and Monica Tibbits-Nutt, Secretary of the MassDOT, shared the State DOT’s vision on AI research and its applications in transportation.
• “Empowering Future Transportation Professionals: Human-Centered AI with Data Integration and Analytics” presented by Muhammad Karim, Postdoctoral Research Associate at UW Smart Transportation Applications & Research Lab (STAR Lab), who focused on workforce development for the next generation of transportation professionals. He shared his personal journey into the world of AI, highlighting the unique challenges and opportunities faced by those without a formal AI background. “ AI and data analytics are game changers for making transportation systems safer and more efficient. It’s important for us to break down the complexities of AI and show newcomers how these tools can be used effectively, ” Muhammad said during his presentation.

During the poster session, PacTrans showcased the work of several student researchers, fostering knowledge exchange among peers and industry experts:

• PhD student Nutvara Jantarathaneewat (UW) presented her research titled, “Detecting Lateral Offset Distance on Rural Roads in Thailand Using Point Cloud Data.” 
• PhD student Bingzhang Wang (UW) presented his research titled, “Traffic Performance GPT (TP-GPT): Real-Time Data Informed Intelligent ChatBot for Transportation Surveillance and Management.”

This symposium served as a pilot effort for the TRB AI for Mobility and Safety (AIMS) Conference scheduled to launch in Seattle in late May 2025. Thank you to all the speakers and presenters for sharing their valuable experiences, and all participants for their dedication and support. 

Read more about the attending student experiences here!

There were many sessions during the symposium, ranging from technical to application-focused, and discussing the challenges of AI in transportation. In my opinion, the most notable session was ‘Empowering Future Transportation Professionals: Understanding Human-Centered AI with Data Integration and Analytics,’ as it aligned with my research. From that session, I had the chance to listen to a lecture on data management, which is crucial in the AI domain. My favorite part of the symposium was the chance to tour the Tesla factory. This tour provided insights into how the largest car factory manages to produce innovative vehicles efficiently and with high quality. Even though most of the content related to car manufacturing, which is outside my field, it prompted me to think about transportation in new ways. For instance, I considered how they prioritize vehicle safety, which is a key component in ensuring road safety.”

– PhD student Nutvara Jantarathaneewat (UW)

I was really into the fireside chat session between Professor Yinhai Wang and Matt Van Horn, the co-founder of several startup companies like Lyft and June. The questions posed in the talk inspired Matt to share many interesting experiences, insightful perspectives and broad visions as a startup founder. The Tesla super factory tour was also an amazing experience where Cybertrucks are assembled on the automated streamline.”

– PhD student Bingzhang Wang (UW)

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Special Sessions On Energy Efficient Computing in Internet of Things

Description.

Energy efficiency stands out as a primary focus for sustainable and eco-friendly IoT networks. As data traffic and network congestion continue to escalate, IoT devices equipped with restricted computational power and energy resources encounter obstacles in analyzing, processing, and storing data. In response to these challenges, computing technology has surfaced as a valuable solution for preserving energy in IoT devices, offering robust computing capabilities, and streamlined storage to facilitate data collection and processing. Consequently, energy-efficient (EE) computing, also known as "green computing," has emerged as a central area of interest for researchers looking to implement IoT solutions.

The topics of interest include (but are not limited to) the following:

The proposed SEEC-IoT special session aims at bringing together researchers from academia and industry to explore and present their findings in Energy-Efficient Computing Solutions for IoT. The participants are encouraged to discuss the theories, systems, technologies, and approaches used to apply those finding in real-word applications. The special session will cover the following topical areas (but not limited to):

• Energy Efficient (EE) Edge, Fog, and Cloud Computing for IoT,
• Energy-Aware IoT Architecture,
• Data Aggregation and Compression for EE IoT,
• Low-Power Hardware and Software Solutions for EE IoT,
• Energy-Aware Scheduling and Task Offloading for IoT,
• Virtualization for EE IoT,
• Energy Harvesting for IoT,
• Artificial Intelligence and Machine Learning for EE IoT,
• Communication Protocols and Algorithms for EE IoT,
• Context Awareness and Autonomous Computing for EE IoT,
• EE Computing for IoT Security, trust, and privacy,
• EE Computing in 6G-enabled IoT Solution

Important Dates

• Deadline for Paper Submissions : July 20th, 2024
• Acceptance Notification : 15th  August, 2024
• Deadline for Camera-Ready Paper Submissions :  8th September, 2024

The submitted paper should be up to six (6) pages in length. The conference allows up to two additional pages for a maximum length of eight (8) pages upon payment of extra page fees once the paper has been accepted.

The paper can be prepared using the template available through the Authors tab from the WF-IoT conference website. An alternative is to use the IEEE Word or Latex templates that can be found at the IEEE provided website here.

Authors of accepted papers will need to provide a final version of their paper in PDF format and upload it by the camera-ready deadline and complete the assignment of copyright and release form. For your paper to be included in the proceedings and published in IEEE Xplore, at least one author is required to register for WF-IoT 2024 by the deadline.

Call For Papers: 

Dr. Zied Bouida, Kuwait College of Science and Technology (KCST), Kuwait

Zied Bouida received the Ph.D. degree in Electrical and Computer Engineering from Concordia University, Montreal, Canada, in 2015. From 2016 to 2023, he was a Senior Research Associate and Cisco Chair Technical Manager at the Internet of Things (IoT) Lab at Carleton University, Ottawa, Canada. He is currently an Assistant Professor at Kuwait College of Science and Technology (KCST), Doha District, Kuwait. His research interests include the modeling, design, and performance analysis of wireless, IoT, and Non-Terrestrial Networks. He is a Senior Member of the IEEE, a Professional Member of the IEEE Honors Society, and a Professional Engineer of Ontario.

Prof. Mohamed Abdallah Trabelsi, Kuwait College of Science and Technology (KCST), Kuwait

Mohamed Trabelsi (IEEE M’10-SM’18) received the B.Sc. degree in Electrical Engineering from INSAT, Tunisia in 2006, M.Sc. in Automated Systems and Ph.D. in Energy Systems from INSA Lyon, France in 2006 and 2009 respectively. From October 2009 to August 2018, he has been holding different Research positions at Qatar University and Texas A&M University at Qatar. In September 2018, he has joined Kuwait College of Science and Technology as an Associate Professor where he is currently a Full Professor and Head of the Electronics and Communications Engineering Department. His research interests include Control Systems with applications arising in the contexts of Power Electronics, Energy Conversion, Renewable Energies Integration, and Smart Grids.

Dr. Ala Abu Alkheir, Lytica, Ottawa, Ontario, Canada

Ala Abu Alkheir is the Director of Analytics at Lytica Inc., bringing a wealth of experience in artificial intelligence, data analysis, and the Internet of Things (IoT). He earned his PhD in Electrical and Computer Engineering from Queen’s University, where he conducted advanced research in signal processing and machine learning. With a solid foundation in both academia and industry, Ala has led numerous innovative projects, driving significant advancements in AI-driven analytics.

His expertise spans a wide range of areas, including developing predictive models, optimizing data workflows, and enhancing decision-making processes through intelligent systems. Ala is also an accomplished educator and has contributed to various academic conferences and workshops, sharing his insights and fostering collaboration among professionals and researchers. As a co-organizer of the IEEE World Forum on IoT, he continues to play a pivotal role in shaping the future of IoT technologies and their applications across different sectors.

Dr. Anis Ben Arfi, Analog Devices Inc., Ottawa, Ontario, Canada

Anis Ben Arfi received his PhD in 2019 from the University of Calgary and currently works at Analog Devices Inc in Ottawa where he focuses on 5G Wireless systems and digital processing algorithms. Anis has been actively volunteering with IEEE where currently serving as a board member of the IEEE Consumer Society representing IEEE Region 7 (Canada).

He is also the vice chair of the IEEE MTT-S Young Professionals. Dr. Anis has participated in several national and international events and conferences and has won prestigious awards.

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PhD Research Topics in Cloud Computing

Cloud computing is known as the universal platform of converged technology.  PhD Research Topics in Cloud Computing  is the junction of advances. In fact, it is the best place to dig essential ideas for your research. At the same time, it is “flexible to adapt new algorithms and mechanisms.”

Main Algorithms

• Machine Learning
• Deep Learning
• Reinforcement Algorithms
• Decision Making

Foremost Mechanisms

• Virtualization
• Softwarization
• Load Balancing
• Resource Management

Initiating your research career in the area of cloud computing is a  ‘smart decision.’  It  reflects a massive success  in your research. Our experts of  PhD Research Topics in Cloud Computing  have 18+ years of experience.   As a matter of fact, we are adept not only in concepts but also in the execution of your research. Below we have listed some of the ground breaking cloud computing projects integrated themes. We can guide to choose best cloud computing research topics for your academic work. We have cloud computing experts to carry end to end research program in cloud computing for your research work.

GROND-BREAKING CLOUD INTEGRATED THEMES

• Vehicular cloud infrastructure
• Software-defined cloud networking
• Cloud-enabled RAN
• Mobile Cloud based IoT
• Virtualized cloud resources
• Adhoc clouds for future 5G
• MapReduce based cloud management
• Cloud with fog architecture
• Blockchain technology in Cloud
• Hybrid cloud technology

Find Your PhD Research Topics in Cloud Computing To Pave Your Own Way Of Research!!!!

On the whole, you can expect more from us since we are here to  satisfy your need  in a short time. With this in mind, we are keen to even in a bit of your work. Thus, it ends up in “good quality in the time of delivery.”

A novel technology of SDCon based Integrated Control Platform for SDNs

Using Workflowsim process to design an Optimized task clustering for mobile cloud computing

On the use of Sparse Matrices to Prevent Information Leakage based on Cloud Computing

The new process of Automated Enforcement for SLA in Cloud Services

An Original Predictive Resource Allocation Structure for Cloud Computing

An effective process of Bibliometric Analysis for Cloud Computing Technology Research scheme

Edge computing system based process on Mobility Support intended for Vehicular Cloud Radio-Access-Networks

An efficient source of Cryptography and Steganography Algorithm used for Cloud Computing

A fresh mechanism for Internet of Things and cloud computing solutions based on mapping study in micro service architectures

Used on Base Station Sleeping intended for Heterogeneous Cloud-Fog Computing Networks

The fresh mechanism for Cloud Resellers based on Bazaar Cloud Markets scheme

Using Face Detection and Fingerprint based on Secure Data in Cloud Computing

An inventive Environmental Study Based on Cloud Computing for Real-Time System

An innovative function of CloudPoS based on Proof-of-Stake Consensus Plan for Blockchain Integrated Cloud system

An innovative system of Hybrid HPC Cloud Strategies from Cluster Competition method

On the use of Cryptography based on Secure Cloud Computing Authentication system

The new process of Research of Fine Grit Access Control Based on Time in Cloud Computing

Using block chain to Build Secure Infrastructure function for Cloud Computing

A fresh function of Prevent Information Leakage in Cloud Computing by Using Sparse Matrices  

An effective function of RIOT based on Stochastic Method used for Workflow Scheduling in the Cloud

MILESTONE 1: Research Proposal

Finalize journal (indexing).

Before sit down to research proposal writing, we need to decide exact journals. For e.g. SCI, SCI-E, ISI, SCOPUS.

Research Subject Selection

As a doctoral student, subject selection is a big problem. Phdservices.org has the team of world class experts who experience in assisting all subjects. When you decide to work in networking, we assign our experts in your specific area for assistance.

Research Topic Selection

We helping you with right and perfect topic selection, which sound interesting to the other fellows of your committee. For e.g. if your interest in networking, the research topic is VANET / MANET / any other

Literature Survey Writing

To ensure the novelty of research, we find research gaps in 50+ latest benchmark papers (IEEE, Springer, Elsevier, MDPI, Hindawi, etc.)

Case Study Writing

After literature survey, we get the main issue/problem that your research topic will aim to resolve and elegant writing support to identify relevance of the issue.

Problem Statement

Based on the research gaps finding and importance of your research, we conclude the appropriate and specific problem statement.

Writing Research Proposal

Writing a good research proposal has need of lot of time. We only span a few to cover all major aspects (reference papers collection, deficiency finding, drawing system architecture, highlights novelty)

MILESTONE 2: System Development

Fix implementation plan.

We prepare a clear project implementation plan that narrates your proposal in step-by step and it contains Software and OS specification. We recommend you very suitable tools/software that fit for your concept.

Tools/Plan Approval

We get the approval for implementation tool, software, programing language and finally implementation plan to start development process.

Pseudocode Description

Our source code is original since we write the code after pseudocodes, algorithm writing and mathematical equation derivations.

Develop Proposal Idea

We implement our novel idea in step-by-step process that given in implementation plan. We can help scholars in implementation.

Comparison/Experiments

We perform the comparison between proposed and existing schemes in both quantitative and qualitative manner since it is most crucial part of any journal paper.

Graphs, Results, Analysis Table

We evaluate and analyze the project results by plotting graphs, numerical results computation, and broader discussion of quantitative results in table.

Project Deliverables

For every project order, we deliver the following: reference papers, source codes screenshots, project video, installation and running procedures.

MILESTONE 3: Paper Writing

Choosing right format.

We intend to write a paper in customized layout. If you are interesting in any specific journal, we ready to support you. Otherwise we prepare in IEEE transaction level.

Collecting Reliable Resources

Before paper writing, we collect reliable resources such as 50+ journal papers, magazines, news, encyclopedia (books), benchmark datasets, and online resources.

Writing Rough Draft

We create an outline of a paper at first and then writing under each heading and sub-headings. It consists of novel idea and resources

Proofreading & Formatting

We must proofread and formatting a paper to fix typesetting errors, and avoiding misspelled words, misplaced punctuation marks, and so on

Native English Writing

We check the communication of a paper by rewriting with native English writers who accomplish their English literature in University of Oxford.

Scrutinizing Paper Quality

We examine the paper quality by top-experts who can easily fix the issues in journal paper writing and also confirm the level of journal paper (SCI, Scopus or Normal).

Plagiarism Checking

We at phdservices.org is 100% guarantee for original journal paper writing. We never use previously published works.

MILESTONE 4: Paper Publication

Finding apt journal.

We play crucial role in this step since this is very important for scholar’s future. Our experts will help you in choosing high Impact Factor (SJR) journals for publishing.

Lay Paper to Submit

We organize your paper for journal submission, which covers the preparation of Authors Biography, Cover Letter, Highlights of Novelty, and Suggested Reviewers.

Paper Submission

We upload paper with submit all prerequisites that are required in journal. We completely remove frustration in paper publishing.

Paper Status Tracking

We track your paper status and answering the questions raise before review process and also we giving you frequent updates for your paper received from journal.

Revising Paper Precisely

When we receive decision for revising paper, we get ready to prepare the point-point response to address all reviewers query and resubmit it to catch final acceptance.

Get Accept & e-Proofing

We receive final mail for acceptance confirmation letter and editors send e-proofing and licensing to ensure the originality.

Publishing Paper

Paper published in online and we inform you with paper title, authors information, journal name volume, issue number, page number, and DOI link

MILESTONE 5: Thesis Writing

Identifying university format.

We pay special attention for your thesis writing and our 100+ thesis writers are proficient and clear in writing thesis for all university formats.

Gathering Adequate Resources

We collect primary and adequate resources for writing well-structured thesis using published research articles, 150+ reputed reference papers, writing plan, and so on.

Writing Thesis (Preliminary)

We write thesis in chapter-by-chapter without any empirical mistakes and we completely provide plagiarism-free thesis.

Skimming & Reading

Skimming involve reading the thesis and looking abstract, conclusions, sections, & sub-sections, paragraphs, sentences & words and writing thesis chorological order of papers.

Fixing Crosscutting Issues

This step is tricky when write thesis by amateurs. Proofreading and formatting is made by our world class thesis writers who avoid verbose, and brainstorming for significant writing.

Organize Thesis Chapters

We organize thesis chapters by completing the following: elaborate chapter, structuring chapters, flow of writing, citations correction, etc.

Writing Thesis (Final Version)

We attention to details of importance of thesis contribution, well-illustrated literature review, sharp and broad results and discussion and relevant applications study.

How PhDservices.org deal with significant issues ?

1. novel ideas.

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To improve the quality and originality of works, we are strictly avoiding plagiarism since plagiarism is not allowed and acceptable for any type journals (SCI, SCI-E, or Scopus) in editorial and reviewer point of view. We have software named as “Anti-Plagiarism Software” that examines the similarity score for documents with good accuracy. We consist of various plagiarism tools like Viper, Turnitin, Students and scholars can get your work in Zero Tolerance to Plagiarism. DONT WORRY ABOUT PHD, WE WILL TAKE CARE OF EVERYTHING.

3. Confidential Info

We intended to keep your personal and technical information in secret and it is a basic worry for all scholars.

• Technical Info: We never share your technical details to any other scholar since we know the importance of time and resources that are giving us by scholars.
• Personal Info: We restricted to access scholars personal details by our experts. Our organization leading team will have your basic and necessary info for scholars.

CONFIDENTIALITY AND PRIVACY OF INFORMATION HELD IS OF VITAL IMPORTANCE AT PHDSERVICES.ORG. WE HONEST FOR ALL CUSTOMERS.

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Startup accelerates progress toward light-speed computing.

• Jun 3, 2024

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Our ability to cram ever-smaller transistors onto a chip has enabled today’s age of ubiquitous computing. But that approach is finally running into limits, with some experts declaring an end to Moore’s Law and a related principle, known as Dennard’s Scaling.

Those developments couldn’t be coming at a worse time. Demand for computing power has skyrocketed in recent years thanks in large part to the rise of artificial intelligence, and it shows no signs of slowing down.

Now Lightmatter , a company founded by three MIT alumni, is continuing the remarkable progress of computing by rethinking the lifeblood of the chip. Instead of relying solely on electricity, the company also uses light for data processing and transport. The company’s first two products, a chip specializing in artificial intelligence operations and an interconnect that facilitates data transfer between chips, use both photons and electrons to drive more efficient operations.

“The two problems we are solving are ‘How do chips talk?’ and ‘How do you do these [AI] calculations?’” Lightmatter co-founder and CEO Nicholas Harris PhD ’17 says. “With our first two products, Envise and Passage, we’re addressing both of those questions.”

We’re going to continue looking at all of the pieces of computers to figure out where light can accelerate them, make them more energy efficient, and faster.

In a nod to the size of the problem and the demand for AI, Lightmatter raised just north of $300 million in 2023 at a valuation of $1.2 billion. Now the company is demonstrating its technology with some of the largest technology companies in the world in hopes of reducing the massive energy demand of data centers and AI models.

"We’re going to enable platforms on top of our interconnect technology that are made up of hundreds of thousands of next-generation compute units,” Harris says. “That simply wouldn’t be possible without the technology that we’re building.”

From Idea to $100K

Prior to MIT, Harris worked at the semiconductor company Micron Technology, where he studied the fundamental devices behind integrated chips. The experience made him see how the traditional approach for improving computer performance—cramming more transistors onto each chip—was hitting its limits.

“I saw how the roadmap for computing was slowing, and I wanted to figure out how I could continue it,” Harris says. “What approaches can augment computers? Quantum computing and photonics were two of those pathways.”

Harris came to MIT to work on photonic quantum computing for his PhD under Dirk Englund, an associate professor in the Department of Electrical Engineering and Computer Science. As part of that work, he built silicon-based integrated photonic chips that could send and process information using light instead of electricity.

The work led to dozens of patents and more than 80 research papers in prestigious journals like Nature . But another technology also caught Harris’s attention at MIT.

“I remember walking down the hall and seeing students just piling out of these auditorium-sized classrooms, watching relayed live videos of lectures to see professors teach deep learning,” Harris recalls, referring to the artificial intelligence technique. “Everybody on campus knew that deep learning was going to be a huge deal, so I started learning more about it, and we realized that the systems I was building for photonic quantum computing could actually be leveraged to do deep learning.”

Harris had planned to become a professor after his PhD, but he realized he could attract more funding and innovate more quickly through a startup, so he teamed up with Darius Bunandar PhD ’19, who was also studying in Englund’s lab, and Thomas Graham MBA ’18. The co-founders successfully launched into the startup world by winning the 2017 MIT $100K Entrepreneurship Competition.

Seeing the Light

Lightmatter’s Envise chip takes the part of computing that electrons do well, like memory, and combines it with what light does well, like performing the massive matrix multiplications of deep-learning models.

“With photonics, you can perform multiple calculations at the same time because the data is coming in on different colors of light,” Harris explains. “In one color, you could have a photo of a dog. In another color, you could have a photo of a cat. In another color, maybe a tree, and you could have all three of those operations going through the same optical computing unit, this matrix accelerator, at the same time. That drives up operations per area, and it reuses the hardware that's there, driving up energy efficiency.”

Passage takes advantage of light’s latency and bandwidth advantages to link processors in a manner similar to how fiber optic cables use light to send data over long distances. It also enables chips as big as entire wafers to act as a single processor. Sending information between chips is central to running the massive server farms that power cloud computing and run AI systems like ChatGPT.

Both products are designed to bring energy efficiencies to computing, which Harris says are needed to keep up with rising demand without bringing huge increases in power consumption.

“By 2040, some predict that around 80 percent of all energy usage on the planet will be devoted to data centers and computing, and AI is going to be a huge fraction of that,” Harris says. “When you look at computing deployments for training these large AI models, they’re headed toward using hundreds of megawatts. Their power usage is on the scale of cities.”

Lightmatter is currently working with chipmakers and cloud service providers for mass deployment. Harris notes that because the company’s equipment runs on silicon, it can be produced by existing semiconductor fabrication facilities without massive changes in process.

The ambitious plans are designed to open up a new path forward for computing that would have huge implications for the environment and economy.

“We’re going to continue looking at all of the pieces of computers to figure out where light can accelerate them, make them more energy efficient, and faster, and we’re going to continue to replace those parts,” Harris says. “Right now, we’re focused on interconnect with Passage and on compute with Envise. But over time, we’re going to build out the next generation of computers, and it’s all going to be centered around light.”

This story was originally published by MIT News .

Image: Courtesy of the researchers. Edited by MIT News

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Singapore looks to boost AI with plans for quantum computing and data centers

Singapore is looking to carve out a global footprint in artificial intelligence (AI) with the release of international standards for large language model (LLM) testing and investments in quantum computing and new data center capacity. 

Quantum has the potential to unlock new value, where higher processing capabilities can be harnessed in areas such as simulating complex molecules for drug discovery, said Deputy Prime Minister Heng Swee Keat at last week's Asia Tech x Singapore 2024 summit. 

Also: Generative AI may be creating more work than it saves

He added that quantum computing can also have synergies with AI, for example, in improving the efficiency of developing and training advanced AI models. This development, in turn, can further drive innovations in deep learning, natural language processing, and computer vision. 

However, there still are challenges to resolve in quantum, including requirements for cryogenic cooling and error correction, Heng said. He noted that researchers worldwide were assessing different approaches to achieve scale and enable quantum computing to be commercially viable. 

Also:  Rote automation is so last year: AI pushes more intelligence into software development  

Singapore wants to address these  challenges with its National Quantum Strategy, coupled with almost SG$300 million ($221.99 million) in investment. This cash is on top of a previous SG$96.6 million commitment  announced in 2022. The new investment is earmarked for five years, through to 2030, to boost the country's position as a leading hub in the development and deployment of quantum technologies, Heng said. 

This roadmap focuses on four areas, including initiatives in quantum research, such as  quantum communications and security and quantum processors, and a scholarship program to produce 100 PhD and 100 master's-level graduates over the next five years, he said. 

Efforts are underway for Singapore to build  capabilities in the design and development of quantum processors . This work will encompass research on  qubit technologies , including photonic networks, neutral atoms, and superconducting circuits.

ZDNET understands Singapore's target is to have the first prototype ready in the next three years and scale out production in five years. 

The government in 2022 unveiled a three-year initiative to build a quantum-safe network that it hopes will showcase "crypto-agile connectivity" and facilitate trials with both public and private organizations. The initiative also includes a quantum security lab for vulnerability research. 

Laying the ground for green data centers

Singapore last week also launched its green data center roadmap to chart "digital sustainability and chart green growth pathways" for such facilities, supporting AI and computing developments. 

The country has over 1.4 gigawatts of data center capacity and is home to more than 70 cloud, enterprise, and co-location data centers.

Singapore is aiming to add at least 300 megawatts of additional data center capacity "in the near term" and another 200 megawatts through green energy deployments, said Janil Puthucheary, senior minister of state for the Ministry of Communications and Information, at the summit. 

Efforts will be made to enhance efficiency through both hardware and software, Puthucheary said, pointing to technologies that maximize energy efficiency and capacity, and green software tools. 

He added that improving data center efficiency is also about greening software, so the carbon emissions of applications can be reduced.

He said the focus will be placed on data centers to accelerate their use of green energy, with the government offering support via grants and incentives to switch to energy-efficient IT equipment. In addition, the Infocomm Media Development Authority (IMDA) will work with PUB to help data centers push their water usage effectiveness (WUE) to 2.0 cubic meters or less per megawatt hour, up from the 2021 median WUE of 2.2 cubic meters. 

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IMDA will jointly develop standards and certifications with industry partners to drive the development and operation of data centers with power usage effectiveness (PUE) of 1.3 or lower. 

In addition, the BCA-IMDA Green Mark for data centers will be refreshed by year-end to raise the standards for energy efficiency in data centers. IMDA will also introduce standards for IT equipment energy efficiency and liquid cooling by 2025, to drive the adoption of these technologies in Singapore.

The green data center roadmap outlines plans to reduce energy use for air-cooling by raising operating temperatures via IMDA's tropical DC methodology . 

According to the government agency, data centers can achieve 2% to 5% energy savings for every 1°C increase in operating temperature.

It also pointed to simulations that have found existing data centers can achieve a 50% reduction in energy consumption of supporting infrastructure, with energy-efficient retrofits and upgrades for key equipment, such as chiller plants and uninterruptible power supplies.

"We aim to uplift all data centers in Singapore to achieve PUE of less than 1.3 at 100% IT load over the next 10 years," IMDA said. "This gives existing data centers sufficient time to plan for upgrades."

The tech industry today emits an estimated 1.5% to 4% of global greenhouse gas emissions, Heng noted, with this figure projected to climb as the use of AI expands alongside the need for data storage and processing. 

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He said technologies that drive the country's digital economy, such as cloud and AI, fuel demand for powerful and energy-intensive computing. 

"Data centers lie at the heart of such activities and require large amounts of energy for processing and cooling. Greening ICT, especially data centers, is therefore crucial in a digital and carbon-constrained world," he said.

"There is a need to balance the economic and social benefits of digital applications with the environmental effects from the resultant emissions," he said, noting that Singapore has committed to a net-zero target by 2050. 

"The [green data center] roadmap sets out low-carbon energy sources that data centers can explore, which include bioenergy, fuel cells with carbon capture, low-carbon hydrogen and ammonia for a start," Puthucheary explained. "We welcome proposals from the industry to push boundaries in realizing these pathways in Singapore."

Charting global test standards for AI models

Meanwhile, the country wants to lead the way by releasing standards for large language model (LLM) testing, developed via partnerships with global organizations such as MLCommons, IBM, and Singtel. 

Dubbed Project Moonshot, the LLM testing tool provides benchmarking, red-teaming, and testing baselines to help developers and organizations mitigate risks associated with LLM deployment. 

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LLMs without guardrails can reinforce biases and create harmful content, with unintended consequences. "IMDA is seeking to establish guardrails to manage the risks while enabling space for innovation," the government agency said. 

"It is important to adopt an agile, test-and-iterate approach to address key risks in model development and use. Project Moonshot provides intuitive results, so testing unveils the quality and safety of a model or application in an easily understood manner, even for a non-technical user."

The testing tool provides a five-tier scoring system where each completed scoring sheet will place the application on a scale. Grade cut-offs can be determined by the author of each of these scoring sheets. 

AI Verify Foundation and MLCommons jointly developed the testing LLM benchmarks. The latter is an open-engineering consortium supported by Qualcomm, Google, Intel, and NVIDIA and recognized by the US National Institute of Science and Technology under its AI Safety Consortium. AI Verify Foundation is Singapore's not-for-profit foundation that focuses on developing AI testing tools. 

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Project Moonshot is currently available as an open beta. 

IMDA said it is working with companies such as Anthropic to develop a practical guide to multilingual and multicultural red-teaming for LLMs. The guide is slated for release later this year for global use.

Artificial Intelligence

Ibm to test southeast asian llm and facilitate localization efforts, rote automation is so last year: ai pushes more intelligence into software development, ready to upskill look to the edge (where it's not all about ai).

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Stanford University School of Medicine blog

How the death of his wife drives data scientist to improve the system

Amir Bahmani, PhD, reached a desperate low in his life following the death of his wife, Someyra, in 2014. Doctors mistook her terrible pain for an inflamed gallbladder, missing the signs of a malignant cancer.

"If they had collected the data, they would have seen that something was going on internally, that there was a big shift underway that occurs with cancer patients," said Bahmani, director of the Stanford Deep Data Research Center . "They might have been able to catch it early and give her a better chance."

In his grief, he realized how much data science could impact medicine and potentially save lives. That's when he resolved to help close that gap and bring the disciplines closer together for the sake of realizing a precision medicine approach -- the type that could have made a difference for Someyra.

"We want to create a common language between engineers, biologists and physicians," said Bahmani, a high-performance computer scientist. "We don't need to know everything, but we need to know enough to communicate efficiently with each other."

We don't need to know everything, but we need to know enough to communicate efficiently with each other. Amir Bahmani

Bahmani was ready to dedicate his life to medicine. But, as an Iranian immigrant without financial means, he faced major obstacles. He had been the first in his class in Iran to obtain a fellowship abroad --  an almost unthinkable possibility -- obtaining a research fellowship at North Carolina State University, where he received a PhD in computer science.

And after battling to obtain visas, Someyra, whom he had met as an undergraduate, was able to join him as a research assistant in engineering at NC State. Together they dreamed of raising a family in America and creating a better life for themselves.

Then came the terrible side pains and suddenly a young husband's worst nightmare was unfurling before his eyes. Someyra was just 26 when she died.

But a grieving Bahmani couldn't have anticipated the challenges he would face in continuing on alone with their shared American dream. After he returned to Iran to bury Someyra, he said he narrowly escaped being drafted into the Iranian army and then also nearly lost his research fellowship because of delays in renewing his visa, which was held up by Iranian authorities.

"In six months, I lost everything. I lost my best friend -- my wife -- and now I was afraid I was going to lose my career," he said. Then, a stroke of good luck: He received a note from the U.S. Embassy in Armenia that his visa awaited him there.

Embracing the challenges

Back in the United States, more tests also awaited him. Bahmani's Iranian background prevented him from working with U.S. national laboratory scientists in high-performance computing. Fortunately, a mentor introduced him to researchers at the Duke Cancer Institute at Duke University School of Medicine.

That would lead him to his first big break: a $10,000 Amazon Web Services (AWS) grant through a program to fight cancer using cloud services, a cost-efficient method for storing and processing large quantities of data. He went on to collaborate with the Duke researchers to publish his first cancer research paper in 2015 on a rapid-fire statistical technique to associate certain cancers with specific mutations.

That introduction to genetics launched Bahmani on a fascinating, if difficult, course. As a computer scientist, the world of genetics seemed daunting. There was so much to be learned. He recalls hearing the term "messenger RNA" from his Duke collaborator early on.

I didn't know what (messenger RNA) was. It's scary when you are in a different field. Amir Bahmani

"I didn't know what it was," he said. "It's scary when you are in a different field."

To expand his knowledge and embrace the challenge, he got an internship that summer at Illumina Inc., which builds computer systems for genetic analysis. He was hired at the Palo Alto, California, company the following year and then joined Stanford Medicine in 2017 as a biomedical data scientist working under the wing of Michael Snyder , PhD, the Stanford W. Ascherman, FACS Professor in Genetics and chair of the Department of Genetics.

That year, Snyder was able to self-diagnose Lyme disease before he had any symptoms by using a wearable device that showed measurable signs of an internal fight with a pathogen. Snyder published a major study on the process, which involved collecting massive quantities of data -- two petabytes, or two million gigabytes.

Bahmani said it was clear they needed a better way to store and process all that data so he turned to cloud computing to help build a system called My Personal Health Dashboard ( MyPHD ) that has since facilitated more than 30 research studies involving over 10,000 participants.

Using the technology, he and his collaborators -- including physicians, geneticists and computer scientists -- developed two algorithms to detect COVID-19 infection as much as seven or eight days before symptoms occur, based on internal changes in the body. They also devised a COVID-19 alert system to warn people early of a developing infection. That work was published in 2022 in Nature Medicine.

Educating with precision

Bahmani wanted to expand the community of people who could work on these complex, multidisciplinary problems. So, with Snyder's help, he developed a course , Cloud Computing for Biology and Healthcare , that included lectures by former Google CEO Eric Schmidt and other luminaries in the field.

"I have always believed that in order to deliver precision medicine, we need to deal with precision education," said Bahmani, now a lecturer in the Department of Genetics. "If anyone around the globe wants to contribute to medicine, they should have a chance."

More recently, he has developed a new certificate program, Fundamentals of Precision Medicine and Cloud Computing , a self-paced curriculum on medicine, genetics and data science for high school, college and graduate students. It begins with lessons on data privacy and moves on to topics such as programming, statistics, cloud computing, artificial intelligence, medical imaging, genomics and wearable devices.

Bahmani is passionate about making these educational opportunities free to underserved students -- those with incomes less than $70,000 -- as he believes these trainees have much to offer the world of medicine.

Moreover, he wants to give back to a system where people like him -- an Iranian immigrant of modest background -- can thrive when given opportunities they wouldn't otherwise have. The program is offered through a nonprofit for which he is seeking additional support.

To truly build trust and establish inclusive healthcare systems, we need to prepare more researchers and experts from underprivileged communities. Amir Bahmani

"To truly build trust and establish inclusive healthcare systems, we need to prepare more researchers and experts from underprivileged communities. We want different voices from different communities," he said.

In the process, he hopes to save more patients from the kind of missteps that took his wife from him.

"This is all done in her memory," he said. "Maybe we can avoid such tragedies for others by detecting these diseases much earlier."

Main image: Jim Gensheimer

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MSE 2024 Graduation Photos

See this slideshow to view our wonderful graduates from Materials, we can’t wait to see where you take your degrees, and are so proud of you.

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Smiles all around for the graduating class.

Graduates' families watching the ceremony.

Beginning of the ceremony.

College of Engineering graduation sign.

Arrival of the graduates.

Graduates getting ready to move their tassels.

Graduation excitement before the big moment.

Filing up to their spots.

A few graduates with director, Elizabeth.

Celebrating the class of 2024!

Jillian Rix Mulligan, winner of the 2024 Division of Materials Science & Engineering Dissertation Award.

Also a big congratulations to Jillian Rix-Mulligan on receiving the 2024 Division of Materials Science & Engineering Dissertation Award for their dissertation, “ Relating Microstructure and Performance of Solid Oxide Cells for Improving Performance and Mitigating Degradation ,” Advisor: Soumendra Basu.

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• SE 2024 Graduation Photos
• Deniz Cetin Wins MSE Outstanding Dissertation of the Year Award
• Yang Yu is Honored With MSE Outstanding PhD Dissertation Award
• First year MSE PhD student awarded Clare Boothe Luce Fellowship

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