Authors : Diwakar Mainali; Megan Nagarkoti; Jebin Dangol; Dipendra Pandit; Ojaswi Adhikari; Dr. Om Prakash Sharma

Volume/Issue : Volume 9 - 2024, Issue 8 - August

Google Scholar : https://shorturl.at/Yo1o5

Scribd : https://tinyurl.com/y8y6fdeb

DOI : https://doi.org/10.38124/ijisrt/IJISRT24AUG519

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Fault tolerance is an important part of cloud computing because it makes sure that services will still be available and reliable even if there is a problem with the hardware, software, or network. The paper talks about a number of different models and strategies for fault tolerance that are used in cloud computing. We look at many important ideas in depth in a literature study. Some of these are redundancy, replication, consensus methods, checkpointing, and failover techniques. As the review pointed out, these methods are used by major cloud service providers like Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure to keep data safe and offer high availability. We talk about new ideas like serverless computing, microservices architecture, and the use of machine learning for fault detection. We also talk about present problems like data consistency, performance overhead, security concerns, and the complexity of fault tolerance models. In the end of the paper, suggestions are made for more research, with a focus on looking into how new technologies affect fault tolerance. There needs to be more actual research to fix the problems with the secondary research, like the small range of literature that was looked at and how quickly cloud technology is growing. The results of this study can help both researchers and professional users who want to make cloud services more reliable by learning more about how to add fault tolerance techniques to cloud systems.

Keywords : Fault Tolerance, Cloud Computing, Redundancy, Replication, Consensus Algorithms, Checkpointing, Failover Mechanisms, Serverless Computing, Microservices, Machine Learning, Data Integrity, High Availability.

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