Entropy-based scheduling performance in real-time multiprocessor systems​

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dc.contributorRincon, Carlos
dc.contributor.authorRivas, Daniel E.
dc.date.accessioned2021-07-07T19:44:26Z
dc.date.available2021-07-07T19:44:26Z
dc.date.issued2021-04-01
dc.description.abstractIn this senior research project, we present the performance analysis of the entropy-based scheduling approach in real-time multiprocessor systems. We analyze the effect of using the entropy-based scheduling layer in deadline-based (global EDF), laxity-based (LLF), and PFair-based (PD2) scheduling algorithms by measuring the number of preemptions, the number of job migrations, and the number of task migrations. The performance comparison results between the selected scheduling algorithms with their entropy-based versions showed that the entropy layer reduces the number of task migrations for all studied algorithms and reduces the number of job migrations for LLF and PD2.
dc.description.departmentComputer Science, Department of
dc.description.departmentHonors College
dc.identifier.urihttps://hdl.handle.net/10657/7809
dc.language.isoen_US
dc.relation.ispartofSummer Undergraduate Research Fellowship
dc.rightsThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.titleEntropy-based scheduling performance in real-time multiprocessor systems​
dc.typePoster

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