Multiprocessor Scheduling Using Nature Inspired Optimization

dc.contributor.guidePanda, Chandra Sekhar
dc.coverage.spatial
dc.creator.researcherNayak, Sasmita Kumari
dc.date.accessioned2023-02-20T12:02:17Z
dc.date.available2023-02-20T12:02:17Z
dc.date.awarded2021
dc.date.completed2021
dc.date.registered2016
dc.description.abstractScheduling is a standout amongst the most essential issues in computational systems. By reason of the growing of end user demand for different types of issues, changing markets with worldwide challenge and quick improvement of new techniques and technologies; the significance of scheduling has grown in a huge scale. There are two cases of the scheduling are there in literature, viz. static and dynamic. Static scheduling needs background knowledge of the tasks to be scheduled to find its execution time. Dynamic task scheduling project does not require any background knowledge of the tasks to be scheduled. The minimization of the make span is the intent of the multiprocessor scheduling problem. Scheduling of tasks in multiprocessor system is an NP-Hard problem. Because of this, a large part of relevant work is based on meta-heuristic approaches with the objective of getting good solutions within a reasonable duration. newline
dc.description.note
dc.format.accompanyingmaterialDVD
dc.format.dimensions30cm
dc.format.extent173p
dc.identifier.urihttp://hdl.handle.net/10603/464925
dc.languageEnglish
dc.publisher.institutionDepartment of Computer Science and Engineering
dc.publisher.placeSambalpur
dc.publisher.universitySambalpur University
dc.relation
dc.rightsuniversity
dc.source.universityUniversity
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Software Engineering
dc.subject.keywordEngineering and Technology
dc.titleMultiprocessor Scheduling Using Nature Inspired Optimization
dc.title.alternative
dc.type.degreePh.D.

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