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Performance Evaluation of Simulated Annealing-Based Task Scheduling Algorithms

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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


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