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A Comparative Study of Energy-Efficient Fault Tolerance Techniques in Cloud Computing

Authors: Shelly Prakash; Dr. Vaibhav Vyas;

A Comparative Study of Energy-Efficient Fault Tolerance Techniques in Cloud Computing

Abstract

With the expansion of cloud computing, ensuring fault tolerance while optimizing energy consumption has become paramount. This paper conducts a comprehensive review of energy-efficient fault tolerance (FT) techniques in cloud computing environments. By analyzing various strategies, mechanisms, and algorithms, this paper aims to provide insights into the state-of-the-art approaches for achieving fault tolerance while minimizing energy consumption. The comparative analysis includes an examination of different FT techniques based on their energy efficiency, reliability, scalability, overhead, and applicability in cloud computing environments. The findings contribute to the understanding of energy-efficient FT techniques and offer guidance for researchers and practitioners in selecting suitable approaches for their specific cloud computing requirements.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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