Cloud Computing Research Project Ideas

Cloud is not real; it is a virtual entity of servers connected within a vast network to operate as a single system. You can learn more on this technology and network when you resume reading this paper.

  1. Define Cloud

The cloud is full of servers each having a unique set of functions connected to a global network. The cloud mentioned here does not mean a physical object; this is a global network with numerous remote servers connected with each other in order to function as a single system.

  1. What is Cloud?

In simple words, cloud is a combination of servers which operates the infrastructure and software which can be operated through internet.

  1. Where Cloud is used?

Cloud is used in maximum of the industries of every size and type for different uses such as email, data backup, software testing and development, disaster recovery, web-applications, big data analytics and virtual desktop.

  1. Why Cloud Technology is proposed? Previous Technology Issues

This technology came into existence, to overcome the drawbacks and challenges faced by previous technology of software deployment models and IT infrastructure. The Cloud technology was proposed mainly to focus on scalability, accessibility and cost efficiency.

The issues faced by previous technology which were overcome by Cloud technology are: Ineffective use of resources, limited accessibility, less scalability, more capital cost, complexity, slow deployment, recovery challenges and loss of data.

  1. Algorithms / Protocols

After knowing about the technology, uses of it and the issues faced by them in the earlier stage, now we are going to learn about the algorithms used for this technology. The algorithms provided for Cloud to overcome the previous issues faced by it like detecting malware in cloud devices are: Anomaly-Based Detection, Signature-Based Detection, Machine Learning and AI-Based Detection, Heuristic-Based Detection and Behavior-Based Detection.

  1. Comparative study / Analysis

Here in this section we are going to compare different approaches, tools and techniques related to this study in order to find the best one foe detecting malware threats in the Cloud network. They are tested using different methodologies to analyze its performance. For analyzing them some of the metrics are required, they are: scalability, execution time, recall, precision, false positive and false negative rates, resource consumption, F1-score and data rates.

  1. Simulation results / Parameters

The approaches which were proposed to overcome the issues faced by Cloud in the above section are to be simulated to perform more effectively and realistic. The different parameters used for it in this study are: Cloud Environment, Data Generation, Evaluation Metrics, Malware Characteristics, Malware Detection Mechanisms, Simulation Tools and Scenarios.

  1. Dataset LINKS / Important URL

Here are some of the links provided for you below to gain more knowledge about Cloud which can be useful for you:

  1. Cloud Applications

The application of Cloud in various fields is now growing faster in the improving technology. Some of the areas in which it is applicable are: Healthcare, Education, Media, gaming, Entertainment, finance and e-commerce.

  1. Topology

Topology is the architecture of a network, how the components of it are organized and arranged within the network. Here in this study based on Cloud, topology defines the flow of data, connection of resources and communication between applications. The common topologies followed by it are: Distributed Cloud Topology, Hybrid Cloud Topology, Interconnected Cloud Topology, Multi-Cloud Topology, Serverless Topology, Private Cloud Topology and Public Cloud Topology.

  1. Environment

The environment in which the Cloud is operating should have some components and key considerations to function in a better way. They are: Disaster Recovery, Cost Management, Backup, Compute Resources, Cloud Service Provider (CSP), Compliance, Expertise, Management Tools, Monitoring, Networking, Training, Security and Storage.

  1. Simulation Tools

Here we provide some simulation software for Cloud, which is established with the usage of tools like CloudSim along with Java of version 1.8, to simulate its performance.

  1. Results

When you have finish reading this research paper completely which is based on the Cloud technology you would have now gained a clear idea about it. You would have now also understood about the applications of it, topologies followed by them, algorithms used and also about some of its limitations.

Cloud Computing Research Project Topics

  1. Building a Layer-2 Hybrid Cloud
  2. Hybrid Cloud Energy Management for Edge Computing
  3. Efficient Secured Cloud Storage System using Dynamic Multiple Clouds Cryptographic Algorithm
  4. Design and Implementation of a Cloud-Network Resource Management System Based on Digital Twin
  5. Initiatives in the Cloud for Government Company Comparing Cloud Providers
  6. Obtaining Cloud Base Height and Phase from Thermal Infrared Radiometry Using a Deep Learning Algorithm
  7. Challenges and Solutions of Public Cloud Carrying 5GC Network
  8. Object as a Service (OaaS): Enabling Object Abstraction in Serverless Clouds
  9. Cloud Instance Resources Prediction Based on Hidden Markov Model
  10. EN-Beats: A Novel Ensemble Learning-Based Method for Multiple Resource Predictions in Cloud
  11. towards a Holistic Cloud System with End-to-End Performance Guarantees
  12. Classification of Cloud Phase Using Combined Ground-Based Polarization Lidar and Millimeter Cloud Radar Observations over the Tibetan Plateau
  13. Trust-Based Secure Multi-Cloud Collaboration Framework in Cloud-Fog-Assisted IoT
  14. Cloud Workload Turning Points Prediction via Cloud Feature-Enhanced Deep Learning
  15. Novel Weight-Improved Particle Swarm Optimization to Enhance Data Security in Cloud
  16. An Advanced Multi-Model Cloud Services using Load Balancing Algorithms
  17. Data Security in Cloud Computation
  18. MockFog 2.0: Automated Execution of Fog Application Experiments in the Cloud
  19. Design-Time Analysis of Time-Critical and Fault-Tolerance Constraints in Cloud Services
  20. Surveillance Drone Cloud and Intelligence Service
  21. Optimized Load Balancing for Green Cloud Computing
  22. Integration and Validation of a Robust Process for Cloud Applications
  23. Security Management Approaches over the Cloud
  24. An Advanced Cloud Security and Load Balancing in Health Care Systems
  25. towards Confidential Computing: A Secure Cloud Architecture for Big Data Analytics and AI
  26. Design of Cloud Service Customer Experience Management System Enhanced by AI
  27. Ingestion of Google Cloud Platform Data using Dataflow
  28. A Multi-Stage Cloud Security for Cloud Data using Amalgamate Data Security
  29. Analysis of Resource Usage Management Plan for Federated Learning in Hybrid Cloud
  30. Composability of Cloud Accelerators in Virtual World Simulations
  31. Secure Lattice-Based Ciphertext-Policy Attribute-Based Encryption from Module-LWE for Cloud Storage
  32. Evaluation Model and Performance Analysis of NIC Aggregations in Containerized Private Clouds
  33. The Use of Cloud Computing and its Security Risks in a Philippine Education System: A Literature Review
  34. Deep Learning Approach for Cost and Storage Optimization of Video Streaming in Cloud Environments
  35. An Efficient User Protected Encryption Storage Algorithm Used in Encrypted Cloud Data
  36. Research on Cloud Side Collaboration Architecture and Lightweight Model of Distribution Network
  37. Secure Cloud Storage using a Digest Algorithm
  38. The next generation of cloud security through hypervisor-based virtual machine introspection
  39. A Research on Various Security Aware Mechanisms in Multi-Cloud Environment for Improving Data Security
  40. MRRA-GAN: Multi-Resolution Relation-Aware GAN for Point Cloud Completion
  41. A Global Perception Attention-based Network for Point Cloud Completion
  42. Point Cloud Completion Cascade Optimization Network Based on Feature Fusion
  43. A Framework for Characterizing Very Large Cloud Workload Traces with Unsupervised Learning
  44. Privacy Regulations-Aware Storage Service Selection in Multi-Cloud
  45. Data Security in AWS S3 Cloud Storage
  46. Securing Data storage in Cloud after Migration using Immutable Data Dispersion
  47. Enabling Efficient Multidimensional Encrypted Data Aggregation for Fog-Cloud-Based Smart Grid
  48. Enabling Scalability in the Cloud for Scientific Workflows: An Earth Science Use Case
  49. A Systematic Approach towards Security Concerns in Cloud
  50. Deep Dive on Various Security Challenges, Threats and Attacks over the Cloud Security