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dc.contributor.authorLee, Ming-Changen_US
dc.contributor.authorLin, Jia-Chunen_US
dc.contributor.authorYahyapour, Raminen_US
dc.date.accessioned2017-04-21T06:55:23Z-
dc.date.available2017-04-21T06:55:23Z-
dc.date.issued2016-06en_US
dc.identifier.issn1045-9219en_US
dc.identifier.urihttp://dx.doi.org/10.1109/TPDS.2015.2463817en_US
dc.identifier.urihttp://hdl.handle.net/11536/133746-
dc.description.abstractIt is cost-efficient for a tenant with a limited budget to establish a virtual MapReduce cluster by renting multiple virtual private servers (VPSs) from a VPS provider. To provide an appropriate scheduling scheme for this type of computing environment, we propose in this paper a hybrid job-driven scheduling scheme (JoSS for short) from a tenant\'s perspective. JoSS provides not only job-level scheduling, but also map-task level scheduling and reduce-task level scheduling. JoSS classifies MapReduce jobs based on job scale and job type and designs an appropriate scheduling policy to schedule each class of jobs. The goal is to improve data locality for both map tasks and reduce tasks, avoid job starvation, and improve job execution performance. Two variations of JoSS are further introduced to separately achieve a better map-data locality and a faster task assignment. We conduct extensive experiments to evaluate and compare the two variations with current scheduling algorithms supported by Hadoop. The results show that the two variations outperform the other tested algorithms in terms of map-data locality, reduce-data locality, and network overhead without incurring significant overhead. In addition, the two variations are separately suitable for different MapReduce-workload scenarios and provide the best job performance among all tested algorithms.en_US
dc.language.isoen_USen_US
dc.subjectMapReduceen_US
dc.subjectHadoopen_US
dc.subjectvirtual MapReduce clusteren_US
dc.subjectmap-task schedulingen_US
dc.subjectreduce-task schedulingen_US
dc.titleHybrid Job-Driven Scheduling for Virtual MapReduce Clustersen_US
dc.identifier.doi10.1109/TPDS.2015.2463817en_US
dc.identifier.journalIEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMSen_US
dc.citation.volume27en_US
dc.citation.issue6en_US
dc.citation.spage1687en_US
dc.citation.epage1699en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000376106400011en_US
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