Topics in Cloud Computing

Topics in Cloud Computing which are latest and advanced are listed below, if you are looking for  Cloud Computing   paper writing help then contact cloudcomputingprojects.net  for best results. Writing a problem statement is an important process, which should describe the potential issue in an explicit manner. By highlighting some major issues in cloud computing, we provide a few instances of problem statement:

1. Enhancing Data Security in Multi-Tenant Cloud Environments Using Homomorphic Encryption

Problem Statement: Regarding data security and confidentiality, problems are raised through the emergence of multi-tenant cloud platforms. For processing missions, data decryption is needed by conventional encryption techniques. However, this process can reveal information to possible violations. By enabling computations on encrypted data excluding the decryption process, the homomorphic encryption provides an ideal solution. But, its extensive implementation is obstructed through its intricacy and high computational cost. Without affecting functionality in a substantial manner, the data security must be improved in multi-tenant cloud platforms. For that, homomorphic encryption methods have to be created and improved, which is the major goal of this study.

2. Dynamic Resource Allocation in Cloud Data Centers Using Machine Learning Algorithms

Problem Statement: For enhancing functionality and cost in cloud data centers, it is important to accomplish effective resource allocation. In the case of varying workloads, the conventional resource allocation techniques cannot adjust in a dynamic manner. It can result in over-provisioning or underuse of resources. For minimizing operational expenses and enhancing usage, this research plans to forecast resource requirements and allocate resources in actual-time dynamically by means of machine learning algorithms. Proper prediction models have to be created. With the cloud infrastructure, these models should be perfectly combined.

3. Improving the Energy Efficiency of Cloud Data Centers through Advanced Load Balancing Techniques

Problem Statement: Ecological implication and high operational expenses are caused by cloud data centers, especially due to their extensive usage of energy. Inappropriate energy utilization is resulted by current load balancing methods because of not considering energy effectiveness. In addition to preserving functionality, energy effectiveness must be considered. For that, improved load balancing algorithms have to be created, which is the significant aim of this study. By enhancing the workload sharing among servers, the energy usage of cloud data centers has to be minimized.

4. Ensuring Data Integrity and Consistency in Cloud Storage Systems Using Blockchain Technology

Problem Statement: In cloud storage frameworks, some of the major problems are data morality and consistency. Across distributed locations, several copies of data are generally stored. In assuring data accessibility and obstructing illicit data alterations, conventional techniques are mostly poor, which are used for guaranteeing data morality and consistency. To improve data morality and consistency in cloud storage frameworks, the application of blockchain mechanism has to be investigated in this study. To manage extensive data storage in an effective manner, a blockchain-related framework should be developed, which is the major challenge.

5. Enhancing Performance of Cloud-Based Big Data Analytics Platforms

Problem Statement: In terms of the intricacy and level of data processing missions, the functionality issues are mostly confronted by big data analytics environments that are specifically presented on the cloud. Relevant to data ingestion, actual-time processing, and storage, problems must be solved. This process has to be conducted to enhance these environments for functionality. With the aim of enhancing throughput and minimizing latency, the functionality of cloud-related big data analytics environments has to be improved by creating algorithms and methods. With cost effectiveness, the functionality enhancements should be stabilized, which is the significant problem.

6. Developing a Robust Cloud Disaster Recovery Solution Using Multi-Cloud Strategies

Problem Statement: For cloud computing platforms, one of the major needs is disaster recovery. At the time of disasters or failures, it is significant to assure business endurance. Vulnerabilities of single points of failure are caused by conventional disaster recovery approaches due to the dependence on a single cloud provider. The major goal of this study is to suggest a multi-cloud disaster recovery policy, which improves strength and reliability by utilizing several cloud providers. In order to assure less data loss and fast recovery, a cost-efficient and robust multi-cloud disaster recovery approach must be created.

7. Optimizing Serverless Computing Performance in Cloud Environments

Problem Statement: Excluding infrastructure management, developers can concentrate on code implementation. This process is enabled by serverless computing that provides cost effectiveness and scalability. Functionality problems like ineffective resource usage and cold start latency mostly impact serverless applications. By creating methods to enhance resource allocation and minimize cold start times, the serverless computing functionality has to be improved in cloud platforms, which is the major goal of this research. While preserving the built-in advantages of serverless frameworks, these enhancements should be accomplished.

8. Implementing Secure Multi-Party Computation in Cloud-Based Collaborative Platforms

Problem Statement: Among several parties, data exchange and joint computation can be enabled by collaborative environments that are presented in the cloud. At the time of collaborative computations, the security and confidentiality of data must be assured, which is still considered as a critical problem. In addition to maintaining the input data confidentiality, parties can assess functions through their inputs in a collaborative manner, specifically by utilizing Secure Multi-Party Computation (SMPC).  To improve data confidentiality and security, the SMPC has to be applied in cloud-related collaborative environments. To adapt with the data intricacy and number of participants, effective SMPC protocol must be created, which is the major challenge.

9. Enhancing Cloud IoT Systems with Edge Computing for Real-Time Data Processing

Problem Statement: When considering the distance among cloud data centers and IoT devices, the latency problems are confronted by cloud-related IoT frameworks. Through conducting computation nearer to the data source, the edge computing provides a solution to enhance actual-time data processing abilities and minimize latency. To improve functionality and responsiveness, the edge computing combination with cloud IoT frameworks must be investigated in this study. To utilize the benefits of edge as well as cloud computing, a perfect integration system has to be created.

10. Comparative Analysis of Serverless vs. Containerized Architectures for Microservices in the Cloud

Problem Statement: For developing feasible and scalable applications, attention is acquired by microservices architecture. For microservices in the cloud, the two general deployments models are containerized and serverless frameworks. On the basis of intricacy, cost, scalability, and functionality, unique benefits and issues are presented in each framework. By considering containerized and serverless frameworks for microservices, this study intends to carry out a comparative analysis process. For various kinds of applications, perceptions have to be offered regarding the relevance of these frameworks. For comparison, explicit criteria must be presented. Among several dimensions, extensive assessments should be carried out.

What topics in computer infrastructure should I make my masters thesis about?

In the domain of computer infrastructure, numerous topics and ideas have evolved in a continuous manner, which are ideal for creating projects. Appropriate for the master’s thesis, we list out some intriguing topics relevant to computer infrastructure:

1. Network Function Virtualization (NFV) and Software-Defined Networking (SDN)

Outline: To enhance network agility, effectiveness, and adaptability, the combination of SDN and NFV has to be investigated.

Possible Research Areas:

• By considering conventional networks and SDN/NFV-based networks, carry out the performance comparison process.
• In SDN/NFV platforms, examine the security problems and solutions.
• Specifically in NFV, consider dynamic resource allocation and optimization methods.
• In service provider or enterprise networks, focus on the placement of SDN/NFV and its case studies.

2. Cloud Computing and Virtualization

Outline: Virtualization mechanisms and different factors of cloud computing must be explored.

Possible Research Areas:

• Consider virtualization methods (containers vs. VMs) and conduct comparative analysis of them.
• In multi-tenant cloud platforms, we plan to explore security and confidentiality issues.
• In cloud data centers, accomplish energy-effective resource handling.
• Focus on cloud-related strategy for business endurance and disaster recovery.

3. Edge and Fog Computing

Outline: In expanding the cloud computing abilities to the network edge, the contribution of fog and edge computing should be analyzed.

Possible Research Areas:

• In edge/fog computing platforms, concentrate on resource handling and scheduling.
• Consider methods for latency minimization in edge/fog computing.
• In edge/fog computing, examine security and confidentiality issues.
• Particularly in smart cities and IoT, explore the application areas of edge/fog computing.

4. High-Performance Computing (HPC) and Parallel Processing

Outline: To facilitate parallel processing and high-performance computing, the suitable algorithms and frameworks have to be investigated.

Possible Research Areas:

• For parallel algorithms on multi-core processors, we intend to explore optimization methods.
• For HPC applications, consider performance evaluation and optimization.
• In HPC frameworks, accomplish energy effectiveness.
• In HPC workloads, examine the application of GPUs and accelerators.

5. Internet of Things (IoT) Infrastructure

Outline: In order to enable extensive IoT placements, the necessary infrastructure must be explored.

Possible Research Areas:

• Examine the IoT networks’ transparency and scalability.
• For IoT data and devices, consider security frameworks.
• With edge and cloud computing, the IoT has to be combined.
• For IoT interaction, concentrate on protocols and principles.

6. Cybersecurity Infrastructure

Outline: To assure efficient cybersecurity techniques, the important infrastructure should be considered.

Possible Research Areas:

• Intrusion detection and prevention systems have to be created and deployed.
• Focus on SIEM (Security information and event management) frameworks.
• Along with efficiency, we aim to investigate network security protocols.
• Consider strategies for incident response and cyber resilience.

7. Blockchain and Distributed Ledger Technologies

Outline: As a means to enable blockchain and other distributed ledger mechanisms, the necessary infrastructure has to be researched.

Possible Research Areas:

• Examine the blockchain networks’ functionality and scalability.
• Concentrate on consensus algorithms. On blockchain effectiveness and protection, study their effect.
• In different industries (such as supply chain, healthcare, and finance), consider the uses of blockchain.
• Specifically in blockchain networks, explore security issues and suggested solutions.

8. Green Computing and Energy Efficiency

Outline: Focus on computing infrastructure and minimize its energy usage by analyzing techniques.

Possible Research Areas:

• Creation and handling of energy-effective data centers.
• Consider green cloud computing policies.
• In data centers, renewable energy must be combined.
• Especially in IT infrastructure, minimize carbon footprint.

9. Software Infrastructure for Big Data Analytics

Outline: To facilitate big data analytics applications, significant infrastructure should be explored.

Possible Research Areas:

• In big data processing systems (for instance: Spark, Hadoop), carry out the performance enhancement process.
• In big data infrastructure, we focus on scalability problems.
• Consider data processing and stream analytics in actual-time.
• For extensive datasets, examine data storage and recovery optimization.

10. Quantum Computing Infrastructure

Outline: Along with infrastructure needs, the evolving area of quantum computing has to be investigated.

Possible Research Areas:

• Quantum algorithms have to be modeled and created.
• Concentrate on fault tolerance and quantum error correction.
• With traditional computing infrastructure, consider the combination of quantum computing.
• In cryptography and enhancement, examine the possible uses of quantum computing.

Sample Research Topic: Energy-Efficient Resource Management in Cloud Data Centers

Problem Statement: Faster development of data centers is resulted through the high requirement for cloud services. Substantial amounts of energy are generally utilized by data centers. In addition to preserving functionality, the power usage of cloud data centers has to be minimized. For that, energy-effective resource management methods must be created, which is the significant goal of this study. Some of the potential concentrations are energy-effective hardware usage, load balancing, and dynamic resource allocation.

Related to the cloud computing domain, several problem statements are offered by us in a clear way. By emphasizing the field of computer infrastructure, we recommended numerous topics which are both important and fascinating.

Hot Thesis Topics in Cloud Computing

Hot Thesis Topics in Cloud Computing on all areas that we have worked are listed below, we will provide complete guidance on these below topics and also give assistance on your own customised topics. We have all the methodologies and professionals  to complete your work on time.

1. Research on the cloud computing fuzzy proportion integration differentiation control strategy for permanent-magnet homopolar motor with salient pole solid rotor used on new-energy vehicle
2. Intrusion detection system in distributed cloud computing: Hybrid clustering and classification methods
3. Security on mobile cloud computing using cipher text policy and attribute based encryption scheme
4. Opposition based sunflower optimization algorithm using cloud computing environments
5. A novel method for intelligent analysis of rice yield traits based on LED transmission imaging and cloud computing
6. A fault tolerance aware green IoT workflow scheduling algorithm for multi-dimensional resource utilization in sustainable cloud computing
7. VM consolidation improvement approach using heuristics granular rules in cloud computing environment
8. Perception and evaluation of selected cloud computing factors in the light of conducted research among small and medium-sized enterprises
9. Design of cloud computing task offloading algorithm based on dynamic multi-objective evolution
10. Integrating big data and cloud computing topics into the computing curricula: A modular approach
11. Study on the non-linear deformation and failure characteristics of EPS concrete based on CT-scanned structure modelling and cloud computing
12. Bee optimization based random double adaptive whale optimization model for task scheduling in cloud computing environment
13. Mobile Cloud computing architecture for massively parallelizable geometric computation
14. The role of cloud computing technology: A saviour to fight the lockdown in COVID 19 crisis, the benefits, characteristics and applications
15. Stable and efficient resource management using deep neural network on cloud computing
16. Evaluation of 5G Edge and Cloud Computing for Data Processing in Visual Referencing of Mobile Robot Manipulators
17. Cloud computing virtual machine consolidation based on stock trading forecast techniques
18. A simulation task partition method based on cloud computing resource prediction using ensemble learning
19. The groundwater potential assessment system based on cloud computing: A case study in islands region
20. Evaluating the benefits of Cloud Computing in Small, Medium and Micro-sized Enterprises (SMMEs)