thesis paper on cloud computing

• DOI: 10.6084/M9.FIGSHARE.1145884
• Corpus ID: 6612474

Cloud Computing: Overview & Current Research Challenges

• Published 2012
• Computer Science, Engineering
• IOSR Journal of Computer Engineering

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Top 10 Cloud Computing Research Topics of 2024

Home Blog Cloud Computing Top 10 Cloud Computing Research Topics of 2024

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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The Impact of Cloud Computing and AI on Industry Dynamics and Concentration

We examine the rise of cloud computing and AI in China and their impacts on industry dynamics after the shock to the cost of Internet-based computing power and services. We find that cloud computing is associated with an increase in firm entry, exit and the likelihood of M&A in industries that depend more on cloud infrastructure. Conversely, AI adoption has no impact on entry but reduces the likelihood of exit and M&A. Firm size plays a crucial role in these dynamics: cloud computing increases exit rates across all firms, while larger firms benefit from AI, experiencing reduced exit rates. Cloud computing decreases industry concentration but AI increases concentration. On the financing side, firms exposed to cloud computing increase equity and venture capital financing, while only large firms increase equity financing when exposed to AI.

We thank Heitor Almeida, Tanya Babina, Jianwei Xing, Keer Yang, and Michael Ewens and seminar participants at the Australia Banking and Finance Conference, the Finance and Organizations (FOM) Conference, the 2023 China Financial Research Conference, the 2024 Midwest Finance Association Conference, Tel Aviv University, and Tsinghua University for their helpful comments. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

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Cloud Computing Thesis Topics

Cloud computing is the architecture in which the host, virtual machines, virtual server, and brokers are involved in communication.  Cloud computing  has various challenges due to its dynamic architecture. These challenges are virtual machine migration, load balancing, task scheduling, and security. The brokers are responsible to assign the cloudlets to the appropriate virtual machine. The selection of the appropriate virtual machine will be decided on the basis of cloudlet which needs to be executed and the resources of the virtual machines. The broker is the intermediated party between the virtual machine and the host. The virtual machines are responsible to execute the cloudlets, verify the identity of the host. There are various topics in cloud computing for thesis and research for M.Tech and Ph.D.

Find the link at the end to download the latest thesis and research topics in cloud computing

The data of the host will be uploaded, deleted or updated on the virtual servers. In recent time, various techniques have been purposes which improved the security of the cloud architecture. These proposed techniques are based on encryption, secure authentication mechanism. The challenges of task allocation and load balancing are accomplished by the techniques which are based on genetic algorithm and bio-inspired techniques. In recent times many users are involved in using cloud services due to which the number of virtual servers, virtual machines are increased to satisfy the demand of users. This leads to an increase in the energy consumption of the cloud architecture. Much research is required to make the cloud architecture energy efficient.

Uses of Cloud Computing

Cloud technology can be used to store files which can later be accessed and retrieved through any web-enabled service. This data can be stored on premises or off premises.

Data Analytics

Cloud technology gives you the option of extracting information from large data sets and patterns to identify customer behavior.

Testing and Development

Cloud technology provides a platform for developer to run and test their applications on the cloud.

Cloud technology gives you the opportunity to store a copy of your files at a distant location. This valuable data is secured and can be accessed whenever a situation arises.

Latest Cloud Computing Topics for thesis and research

Masters students can opt for this topic for their thesis. It has a number of fields to work on and for research. Here is the list of topics in cloud computing for thesis as well as for research:

Cloud Deployment Model:

The four main cloud deployment models are public cloud, private cloud, hybrid cloud, and community cloud. Public cloud is a cloud platform which is under the control of the third-party provider. This cloud model is available for public use in accordance with the pay-per-use concept. In this, the customers only pay for the resources they are using. Private cloud is under the ownership of a single organization. It is mainly for the specific use of the organization. Its architecture is different from that of the public cloud. Hybrid cloud comprises of two or more different cloud models. The cloud models retain their individual entity. The architecture of this complex to deploy. The community cloud is more or less like a public cloud but it is for the specific community of cloud users. This a very good topic for a thesis for M.Tech students.

Cloud Service Model:

Cloud Service is the collection of cloud services IaaS(Infrastructure as a Service), PaaS(Platform as a Service), SaaS(Software as a Service). In IaaS, infrastructure resources like the server, storage, and networking are provided to the users by the vendors. This reduces the hardware cost and the users pay only for the resources they use. PaaS allows users to develop, manage and deploy applications on the underlying infrastructure. Users can also test their applications. SaaS provides users the ability to use the deployed applications and software. The main example of this is the email and calendar. This was just an overview of the cloud services. You will get to explore more of the service model if you opt for this topic for your thesis or for your research.

Big data is a term used to denote the large volume of data which may be structured or unstructured. Structured data is the organized data while unstructured data is an unorganized form of data. Big data is characterized by 3Vs namely volume, variety and velocity. Volume refers to a large volume of data handled with technologies like Hadoop. Variety means different format of data. Velocity means the speed with which the data is generated. Big data is used to get useful insights from a company or an organization. The data is complex to manage and is growing day by day. The data can be used by the organization to detect failures, issues, cost, time and to make smart decisions based on that. It has become a trending topic for thesis combined with Hadoop.

Green Cloud Computing:

Green Cloud Computing is a very broad field and a hot topic for the thesis. Green Cloud Computing tend to make virtualized data centers and servers in order to be more energy efficient. The IT resources are consuming so much power and energy leading to a shortage of energy and affecting the global climate. Green cloud computing provide solutions to make IT resources more energy efficient and to reduce operational costs. Green cloud computing focuses on power management, virtualization of servers, recycling and environment sustainability. It is one of the trending thesis topics in cloud computing.

Cloud Security:

Cloud Security refers to certain policies and security measures to protect data, applications, and infrastructure of the cloud environment. There are certain issues in the cloud when storing data in third-party data centers. There are threats to confidentiality, access, and integrity of data. It is also a broad area. One can write a thesis on cloud computing security.

Cloud cryptography

Cloud cryptography is a type of secure cloud computing architecture. It means using encoding techniques to secure data for a long time which is stored in a cloud system. Cloud computing is distributed on a large scale in computing models. The main purpose of using cloud computing is to protect the data for the user and to transmit it at faster speed whenever needed. one can access resources externally by using different terminals. There are millions of terminal for different users with the private key. The private key is used only as a security point of view. one has many options to secure data in this system. A user can also secure data using encryption format in cloud computing. By using cloud computing as a thesis topic, one can get various topics option.

Cloud Computing Platforms

It is another wide field in cloud computing in which you can study various cloud computing platforms for your thesis and research work. In this, you will get to know the current leaders providing cloud-based services like Amazon, IBM, Microsoft. Microsoft Azure is the cloud-based service provided by Microsoft. AppEngine of Google provides cloud services targeting web developers and web hosting applications.

Mobile Cloud Computing

Mobile Cloud Computing is a type of cloud computing which involves the use of mobile devices. In this, the storage and processing of data take place outside the mobile device. It is one of the hot topics in cloud computing for thesis and research. The major advantage of mobile cloud computing is that there is no need for complex and costly hardware along with extended battery life. Data storage capacity and processing power are also improved in mobile cloud computing. No doubt mobile cloud computing has certain advantages, it has certain issues in the form of low bandwidth and heterogeneity.

Edge Computing:

Edge Computing is a computing infrastructure in which the data is processed at the edge of the network instead of the data warehouse. In other words, data is processed nearer to the source. It is more or less related to fog computing. As compared to cloud computing, edge computing is a relatively new field. It overcomes the shortcomings of cloud computing. It optimizes resource usage in cloud computing systems and also improves the security of the system. It is also a good thesis topic for cloud computing.

Along with these topics, some other topics in cloud computing can be Cloud-based  IoT , cloud migration, virtualization and cloud architecture.

These were the latest thesis topics in cloud computing for M.Tech and Ph.D.

The scope of Cloud Computing

Cloud Computing is a relatively new field with a bright future. Everyone is not aware of this technology. Cloud Computing jobs are also rising in the IT sector.  Cloud Computing  is also being taught as a subject in academics. It is a trending topic for M.Tech thesis paper and research. Cloud Computing is the future of the business. All the techno giants are tending towards this emerging technology due to its various advantages.

• Skills required for a career in Cloud Computing

Technical Skills

Exceptional programming skills, data analysis skills, financial skills, project mangement skills, internet security.

If you have these skills then you are eligible for making a successful career in cloud computing.

Techsparks  provide help for the thesis in cloud computing. You can  contact us  if you need thesis topic suggestion in cloud computing for M.Tech and Ph.D. The experts at Techsparks can suggest more thesis topics in cloud computing. You can contact us at  +91-9465330425  or email us at  [email protected]  for any thesis-related help in cloud computing. You can also fill the query form on the website to get in touch with Techsparks.

Click on the following link to download the latest thesis and research topics in cloud computing

• Latest Thesis and Research Topics in Cloud Computing(pdf)

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CS students received the Jay Lepreau Best Paper Award

8/7/2024 Bruce Adams

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Illinois CS students and faculty, with their collaborators, received the Jay Lepreau Best Paper Award at the 18th USENIX Symposium on Operating Systems Design and Implementation (OSDI ‘24). OSDI, the premier conference on computer systems research, selects three best papers each year after a double-blind review. The paper presents a framework called Anvil for building formally verified cluster management controllers.

Written by Bruce Adams

Illinois CS students and faculty, together with their collaborators, received the Jay Lepreau Best Paper Award at the 18th USENIX Symposium on Operating Systems Design and Implementation (OSDI ‘24). OSDI, the premier conference on computer systems research, selects three best papers each year after a double-blind review.

The paper, titled “ Anvil: Verifying Liveness of Cluster Management Controllers ,” presents a framework called Anvil for building formally verified cluster management controllers. It is the first tool to apply formal verification to the problem of controller correctness, with a general specification called Eventually Stable Reconciliation (ESR), written as a concise temporal logic liveness property. With Anvil, developers can write controller implementations in Rust and verify that the controllers correctly implement ESR. Anvil also supports the verification of safety properties. The team used Anvil to verify three Kubernetes controllers, which can readily be deployed in Kubernetes platforms and are comparable in terms of features and performance to widely used unverified controllers.

The project is led by Xudong Sun , a fifth-year PhD student at the Siebel School of Computing and Data Science, working with Wenjie Ma (a visiting undergraduate student at Illinois, Jiawei Tyler Gu (CS PhD student), and Zicheng Ma (an undergraduate student from ZJUI participating in CS Summer Research Program ), and CS professor Tianyin Xu , in collaboration with Tej Chajed from the University of Wisconsin-Madison, Jon Howell, Andrea Lattuada, Oded Padon and Adriana Szekeres from VMware Research, and Lalith Suresh from Feldera.

Sun presented the paper in July at OSDI in Santa Clara, CA, and the work was very well received. Mooly Sagiv, the Chair of Software Systems at Tel Aviv University and a Fellow of the ACM, called the paper “A major achievement for formal verification.” Dominik Tornow, the author of “Think Distributed Systems,” wrote, “Brilliant work and fantastic paper.” The team has been invited to seminars and workshops at Google, Microsoft, and VMware.

“It is very challenging to build provably correct software systems that are practical and readily deployable in real-world cloud/datacenter infrastructures.” says Xu, “The research is very interdisciplinary across computer systems and formal methods.”

Sun attributes the success to the “dream team” he has been working with and learning from. The team represents people from industrial research and academia, with experts in cluster management, distributed computing theory and practice, programming languages, formal verification theory and practice, testing, and systems reliability.

Suresh, CEO and Co-founder of Feldera, and a core member of the project, said, “Practical systems verification is a lofty goal, and you need a highly interdisciplinary team like this one to push the frontier.”

The paper is the result of Sun’s continuous research on testing and verification of cloud infrastructure systems over the past four years. Before Anvil, he had developed the successful testing tools Sieve and Acto , which found hundreds of serious bugs in critical infrastructure code that led to system outages, data loss, and security vulnerabilities. The recent outages caused by bugs in a CrowdStrike security update affected people worldwide and are as vivid an example as needed to demonstrate how minor errors in coding can have serious consequences.

“We are very successful in finding important bugs by testing, but I hope to go one step further – proving that there are no more bugs in these critical systems.” Sun states, “Our vision is to build provably correct cloud infrastructures through formal verification.”

Anvil is only the first step towards Sun’s ambitious research vision. The team will continue to push the boundaries towards probably correct and practical cloud/data center infrastructures.

Sun is entering his final year as a PhD student at Illinois. He plans to find a faculty job and continue this exciting research. As a  Mavis Future Faculty Fellow , he is well prepared.

“Xudong is exceptional and is among the best junior researchers I have worked with in my career,” says Xu. “He always targets deep, fundamental problems, thinks deeply and critically, and knows how to work with and learn from his colleagues and team members. I have no doubt that he will be a fantastic professor in the near future.”

Lalith Suresh, CEO/Co-founder at Feldera, tweeted that “The star of the show was Xudong Sun, the lead PhD student on the project, who had to work at the intersection of ALL those areas above! He is absolutely *fearless*, one of the key marker traits of a successful systems researcher. Xudong will be on the academic and industrial research job market this year -- if you're on a hiring committee, you'd be foolish not to hire him.”

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This story was published August 7, 2024.

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Tracking emissions to help companies reduce their environmental footprint

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Amidst a global wave of corporate pledges to decarbonize or reach net-zero emissions, a system for verifying actual greenhouse gas reductions has never been more important. Context Labs, founded by former MIT Sloan Fellow and serial entrepreneur Dan Harple SM ’13, is rising to meet that challenge with an analytics platform that brings more transparency to emissions data.

The company’s platform adds context to data from sources like equipment sensors and satellites, provides third-party verification, and records all that information on a blockchain. Context Labs also provides an interactive view of emissions across every aspect of a company’s operations, allowing leaders to pinpoint the dirtiest parts of their business.

“There’s an old adage: Unless you measure something, you can’t change it,” says Harple, who is the firm’s CEO. “I think of what we’re doing as an AI-driven digital lens into what’s happening across organizations. Our goal is to help the planet get better, faster.”

Context Labs is already working with some of the largest energy companies in the world — including EQT, Williams Companies, and Coterra Energy — to verify emissions reductions. A partnership with Microsoft, announced at last year’s COP28 United Nations climate summit, allows any organization on Microsoft’s Azure cloud to integrate their sensor data into Context Lab’s platform to get a granular view of their environmental impact.

Harple says the progress enables more informed sustainability initiatives at scale. He also sees the work as a way to combat overly vague statements about sustainable practices that don’t lead to actual emissions reductions, or what’s known as “greenwashing.”

“Just producing data isn’t good enough, and our customers realize that, because they know even if they have good intentions to reduce emissions, no one is going to believe them,” Harple says. “One way to think about our platform is as antigreenwashing insurance, because if you get attacked for your emissions, we unbundle the data like it’s in shrink-wrap and roll it back through time on the blockchain. You can click on it and see exactly where and how it was measured, monitored, timestamped, its serial number, everything. It’s really the gold standard of proof.”

An unconventional master’s

Harple came to MIT as a serial founder whose companies had pioneered several foundational internet technologies, including real-time video streaming technology still used in applications like Zoom and Netflix, as well as some of the core technology for the popular Chinese microblogging website Weibo.

Harple’s introduction to MIT started with a paper he wrote for his venture capital contacts in the U.S. to make the case for investment in the Netherlands, where he was living with his family. The paper caught the attention of MIT Professor Stuart Madnick, the John Norris Maguire Professor of Information Technology at the MIT Sloan School of Management, who suggested Harple come to MIT as a Sloan Fellow to further develop his ideas about what makes a strong innovation ecosystem.

Having successfully founded and exited multiple companies, Harple was not a typical MIT student when he began the Sloan Fellows program in 2011. At one point, he held a summit at MIT for a group of leading Dutch entrepreneurs and government officials that included tours of major labs and a meeting with former MIT President L. Rafael Reif.

“Everyone was super enamored with MIT, and that kicked off what became a course that I started at MIT called REAL, Regional Entrepreneurial Acceleration Lab,” Harple says. REAL was eventually absorbed by what is now REAP — the Regional Entrepreneurship Acceleration Program, which has worked with communities around the world.

Harple describes REAL as a framework vehicle to put his theories on supporting innovation into action. Over his time at MIT, which also included collaborating with the Media Lab, he systematized those theories into what he calls pentalytics, which is a way to measure and predict the resilience of innovation ecosystems.

“My sense was MIT should be analytical and data-driven,” Harple says. “The thesis I wrote was a framework for AI-driven network graph analytics. So, you can model things using analytics, and you can use AI to do predictive analytics to see where the innovation ecosystem is going to thrive.”

Once Harple’s pentalytics theory was established, he wanted to put it to the test with a company. His initial idea for Context Labs was to build a verification platform to combat fake news, deepfakes, and other misinformation on the internet. Around 2018, Harple met climate investor Jeremy Grantham, who he says helped him realize the most important data are about the planet. Harple began to believe that U.S. Environmental Protection Agency (EPA) emissions estimates for things like driving a car or operating an oil rig were just that — estimates — and left room for improvement.

“Our approach was very MIT-ish,” Harple says. “We said, ‘Let’s, measure it and let’s monitor it, and then let’s contextualize that data so you can never go back and say they faked it. I think there’s a lot of fakery that’s happened, and that’s why the voluntary carbon markets cratered in the last year. Our view is they cratered because the data wasn’t empirical enough."

Context Labs’ solution starts with a technology platform it calls Immutably that continuously combines disparate data streams, encrypts that information, and records it on a blockchain. Immutably also verifies the information with one or more third parties. (Context Labs has partnered with the global accounting firm KPMG.)

On top of Immutably, Context Labs has built applications, including a product called Decarbonization-as-a-Service (DaaS), which uses Immutably’s data to give companies a digital twin of their entire operations. Customers can use DaaS to explore the emissions of their assets and create a verification or certificate of the quantified carbon intensity of their products.

Putting emissions data into context

Context Labs is working with oil and gas companies, utilities, data centers, and large industrial operators, some using the platform to analyze more than 3 billion data points each day. For instance, EQT, the largest natural gas producer in the U.S., uses Context Labs to verify the carbon intensity of its operational assets and refine its overall GHG emissions mitigation strategy. Other customers include the nonprofits Rocky Mountain Institute and the Environmental Defense Fund.

“I often get asked how big the total addressable market is,” Harple says. “My view is it’s the largest market in history. Why? Because every country needs a decarbonization plan, along with instrumentation and a digital platform to execute, as does every company.”

With its headquarters in Kendall Square in Cambridge, Massachusetts, Context Labs is also serving as a test for Harple’s pentalytics theory for innovation ecosystems. It also has operations in Houston and Amsterdam.

“This company is a living lab for pentalytics,” Harple says. “I believe Kendall Square 1.0 was factory buildings, Kendall Square 2.0 is biotech, and Kendall Square 3.0 will be climate tech.”

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