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dc.contributor.authorKaya, K.en_US
dc.contributor.authorUçar, B.en_US
dc.contributor.authorAykanat, C.en_US
dc.date.accessioned2016-02-08T10:07:42Z
dc.date.available2016-02-08T10:07:42Z
dc.date.issued2008en_US
dc.identifier.issn1860949X
dc.identifier.urihttp://hdl.handle.net/11693/23006
dc.description.abstractWe consider the problem of scheduling an application on a computing system consisting of heterogeneous processors and one or more file repositories. The application consists of a large number of file-sharing, otherwise independent tasks. The files initially reside on the repositories. The interconnection network is heterogeneous. We focus on two disjoint problem cases. In the first case, there is only one file repository which is called as the master processor. In the second case, there are two or more repositories, each holding a distinct set of files. The problem is to assign the tasks to the processors, to schedule the file transfers from the repositories, and to order the executions of tasks on each processor in such a way that the turnaround time is minimized. This chapter surveys several solution techniques; but the stress is on our two recent works [22,23]. At the first glance, iterative-improvement-based heuristics do not seem to be suitable for the aforementioned scheduling problems. This is because their immediate application suggests iteratively improving a complete schedule, and hence building and exploring a complex neighborhood around the current schedule. Such complex neighborhood structures usually render the heuristics time-consuming and make them stuck to a part of the search space. However, in both of the our recent works, we show that these issues can be solved by using a three-phase approach: initial task assignment, refinement, and execution ordering. The main thrust of these two works is that iterative-improve-based heuristics can efficiently deliver effective solutions, implying that iterative-improve-based heuristics can provide highly competitive solutions to the similar scheduling problems. © 2008 Springer-Verlag Berlin Heidelberg.en_US
dc.language.isoEnglishen_US
dc.source.titleStudies in Computational Intelligenceen_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/978-3-540-69277-5_5en_US
dc.subjectHeterogeneous platformsen_US
dc.subjectIterative-improvement heuristicsen_US
dc.subjectNeighborhood explorationen_US
dc.subjectScheduling file-sharing tasksen_US
dc.titleAdapting iterative-improvement heuristics for scheduling file-sharing tasks on heterogeneous platformsen_US
dc.typeArticleen_US
dc.departmentDepartment of Computer Engineering
dc.citation.spage121en_US
dc.citation.epage151en_US
dc.citation.volumeNumber146en_US
dc.identifier.doi10.1007/978-3-540-69277-5_5en_US


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