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dc.contributor.authorMoulik, Sanjay
dc.contributor.authorDas, Zinea
dc.contributor.authorDevaraj, Rajesh
dc.contributor.authorChakraborty, Shounak
dc.date.accessioned2021-09-03T08:56:03Z
dc.date.available2021-09-03T08:56:03Z
dc.date.created2020-12-13T22:52:28Z
dc.date.issued2020
dc.identifier.citationJournal of systems architecture. 2020, .en_US
dc.identifier.issn1383-7621
dc.identifier.urihttps://hdl.handle.net/11250/2772773
dc.description.abstractOver the years, the nature of processing platforms is witnessing a significant shift in most of the battery supported real-time systems, which now support a combination of specialized multicores to meet the demands of modern applications. Devising energy-efficient schedulers has become a critical issue for such kinds of devices. Hence, this research presents a low-overhead heuristic strategy named SEAMERS, for DVFS based energy-aware scheduling for a set of real-time periodic tasks on a heterogeneous multicore platform. The presented strategy operates in four phases, namely Deadline Partitioning, Core Clustering, Task Allocation and Energy-Aware Scheduling. Our experimental analysis shows that the presented strategy improves upon the state-of-the-art in terms of energy savings (16% to 47% on average) and enables significant improvement in resource utilization.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.titleSEAMERS: A Semi-partitioned Energy-Aware scheduler for heterogeneous MulticorEReal-time Systemsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber0en_US
dc.source.journalJournal of systems architectureen_US
dc.identifier.doi10.1016/j.sysarc.2020.101953
dc.identifier.cristin1859270
dc.description.localcodeThis article will not be available due to copyright restrictions (c) 2020 by Elsevieren_US
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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