Performance Evaluation of Simulated Annealing-Based Task Scheduling Algorithms

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DC Field	Value	Language
dc.contributor.author	Mishra, Abhishek	-
dc.date.accessioned	2024-05-07T04:14:56Z	-
dc.date.available	2024-05-07T04:14:56Z	-
dc.date.issued	2020-09	-
dc.identifier.uri	https://link.springer.com/chapter/10.1007/978-981-15-4936-6_15	-
dc.identifier.uri	http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/14740	-
dc.description.abstract	The performance of simulated annealing (SA)-based task scheduling algorithms is evaluated. First, various parameters of SA are varied, and it is seen how it affects the schedule length (SL). The parameters that are varied are initial temperature, number of iterations, initial clustering, and cooling schedule. Then, one SA-based task scheduling algorithm is selected and compared with other task scheduling algorithms. The algorithms selected for comparison are cluster pair priority scheduling (CPPS), dominant sequence clustering (DSC), edge zeroing (EZ), and linear clustering (LC). Random task graphs are used for comparison	en_US
dc.language.iso	en	en_US
dc.publisher	Springer	en_US
dc.subject	Computer Science	en_US
dc.subject	Simulated Annealing (SA)	en_US
dc.subject	Cluster Pair Priority Scheduling (CPPS)	en_US
dc.subject	Dominant Sequence Clustering (DSC)	en_US
dc.title	Performance Evaluation of Simulated Annealing-Based Task Scheduling Algorithms	en_US
dc.type	Article	en_US
Appears in Collections:	Department of Computer Science and Information Systems

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