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dc.contributor.authorLin, Jia-Chunen_US
dc.contributor.authorLeu, Fang-Yieen_US
dc.contributor.authorLee, Ming-Changen_US
dc.contributor.authorChen, Ying-pingen_US
dc.date.accessioned2014-12-08T15:33:48Z-
dc.date.available2014-12-08T15:33:48Z-
dc.date.issued2013en_US
dc.identifier.isbn978-0-7695-4952-1978-1-4673-6239-9en_US
dc.identifier.urihttp://hdl.handle.net/11536/23357-
dc.identifier.urihttp://dx.doi.org/10.1109/WAINA.2013.10en_US
dc.description.abstractMapReduce as a master-slave infrastructure consists of two master-side severs and a large number of slave-side working nodes. In this paper, we derive a job completion reliability (JCR for short) model from a single-job perspective for a general MapReduce infrastructure in which no redundancy scheme is adopted on the master side, and a cold-standby scheme is employed on the slave side. Without loss of generality, the JCR model is derived based on a Poisson distribution. In addition, we calculate the corresponding job energy consumption (JEC for short). Through the simulation and analytical results, MapReduce managers and service providers can comprehend how this infrastructure behaves and how to improve the infrastructure so as to achieve a more reliable and energy-efficient MapReduce environment.en_US
dc.language.isoen_USen_US
dc.subjectMapReduceen_US
dc.subjectmaster-slave infrastructureen_US
dc.subjectjob completion reliabilityen_US
dc.subjectjob energy consumptionen_US
dc.subjectsingle-job perspectiveen_US
dc.subjectPoisson distributionen_US
dc.titleDeriving Job Completion Reliability and Job Energy Consumption for a General MapReduce Infrastructure from Single-Job Perspectiveen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1109/WAINA.2013.10en_US
dc.identifier.journal2013 IEEE 27TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS WORKSHOPS (WAINA)en_US
dc.citation.spage1642en_US
dc.citation.epage1647en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000327181600268-
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