Energy efficient fault tolerance techniques in green cloud computing: A systematic survey and taxonomy

Salil Bharany, Sumit Badotra, Sandeep Sharma, Shalli Rani, Mamoun Alazab, Rutvij H. Jhaveri, Thippa Reddy Gadekallu

Research output: Contribution to journalReview articlepeer-review

Abstract

Cloud computing has brought the accessibility of several software platforms under a single roof. It has transformed resources into scalable services on demand and provides the only solution to the high resource requirements. All cloud service providers usually offer all types of services in the cloud computing environment, even though they also handle security-related challenges like reliability, availability, and throughput. One of the most decisive challenges in the cloud is handling faults. High fault tolerance in the cloud is a must to attain high performance, and the defects must be investigated and examined for future guidance. The principal target of this paper is to gain insight into the fault tolerance techniques that are available to us and the challenges that are required to be overcome. We concluded that there is always a relation between faults and energy consumption during our survey. If there is a high potential to tolerate a fault, there will be a need for more infrastructure and devices to fix those faults, which further leads to more power consumption. In this paper, 129 Research papers published through February 2022 were considered and further classified. This paper critically reviews techniques to tolerate faults in cloud computing systems and discusses the taxonomy of errors, faults, and failures. Furthermore, this paper aims to investigate several critical research topics and advanced techniques, such as artificial intelligence, deep learning, the Internet of Things, and machine learning, that may be employed as an intelligent fault tolerance strategy in the cloud environment.

Original languageEnglish
Article number102613
Pages (from-to)1-15
Number of pages15
JournalSustainable Energy Technologies and Assessments
Volume53
DOIs
Publication statusPublished - Oct 2022

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