Critical review of scheduling algorithms to optimize datacentre energy consumption and environmental impact towards green cloud computing

Jha, Pankhuri (2022) Critical review of scheduling algorithms to optimize datacentre energy consumption and environmental impact towards green cloud computing. Masters thesis, Dublin, National College of Ireland.

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Abstract

Computing research has increasingly migrated toward green computing. The wide use of technology presents certain environmental issues such as excessive power use and a growing carbon footprint that harms the atmosphere. Therefore, for cloud service providers maintaining the Quality of Service (QoS) and service level agreements (SLAs) while reducing energy usage and resource productivity became very difficult.

The objective of this paper is to analyse scheduling algorithms to optimize resource utilization and to provide high-quality service in a cloud computing data centre which goes through effective resource scheduling algorithms to deliver the benefits of low energy consumption.

Hence, comparison of different resource scheduling like load based, temperature based, and other types of algorithms with respect to different parameters like execution time, response time, load balance and make span of job has been done to find the best resource scheduling algorithm. Therefore, in order to provide effective execution of user jobs a lot of effort has been put in determining the priority of jobs and timing constraints using python. Focus is put on allocating the relevant priorities while consuming less time and energy. With the analysis it could be said round robin scheduling algorithms can effectively increase resource utilization while reducing the energy consumption for job execution because it’s better for interactive application as the response time is lesser.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Sahni, Vikas UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Cloud computing Q Science > QA Mathematics > Algebra > Algorithms > Computer algorithms T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Electricity Supply
Divisions:	School of Computing > Master of Science in Cloud Computing
Depositing User:	Tamara Malone
Date Deposited:	18 Apr 2023 18:04
Last Modified:	18 Apr 2023 18:04
URI:	https://norma.ncirl.ie/id/eprint/6472

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