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Pfairness Applied to EDF to Reduce Migration Overheads and Improve Task Schedulability in Multicore Platforms

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dc.contributor.author K., Pradheep Kumar
dc.date.accessioned 2023-01-17T11:09:43Z
dc.date.available 2023-01-17T11:09:43Z
dc.date.issued 2009
dc.identifier.uri https://ieeexplore.ieee.org/document/5366280
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8528
dc.description.abstract This paper proposes a scheduler combining the concepts of EDF and pfairness using the worst fit heuristic function. In scheduling algorithms without pfairness, priority is not monitored closely in case of preemptions. An algorithm combining EDF and pfairness proposed in this paper overcomes this drawback. Here resources are granted in accordance to the task weight. Individually using either EDF or pfairness utilizes the resources to a greater extent, whereas a combination of both achieves better reduction in migration overheads. The algorithm has been simulated on Cheddar, a real time scheduling tool, and also on SESC, an architectural simulator on multicore platforms. The algorithm presented in this paper has been tested for 5000 random task sets. The results show that it reduces the migration overhead by 33% for partitioned task sets and by 38 % for hybrid task sets, and improves task schedulability by 37%, compared to conventional EDF. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject Computer Science en_US
dc.subject EDF en_US
dc.subject Scheduling en_US
dc.subject Migration overhead en_US
dc.subject Task schedulability en_US
dc.subject SESC en_US
dc.title Pfairness Applied to EDF to Reduce Migration Overheads and Improve Task Schedulability in Multicore Platforms en_US
dc.type Article en_US


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