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Article: Optimization of Composite Cloud Service Processing with Virtual Machines

TitleOptimization of Composite Cloud Service Processing with Virtual Machines
Authors
Issue Date2015
PublisherIEEE.
Citation
IEEE Transactions on Computers (In press), 2015 How to Cite?
AbstractBy leveraging virtual machine (VM) technology, we optimize cloud system performance based on refined resource allocation, in processing user requests with composite services. Our contribution is three-fold. (1) We devise a VM resource allocation scheme with a minimized processing overhead for task execution. (2) We comprehensively investigate the best-suited task scheduling policy with different design parameters. (3) We also explore the best-suited resource sharing scheme with adjusted divisible resource fractions on running tasks in terms of Proportional-Share Model (PSM), which can be split into absolute mode (called AAPSM) and relative mode (RAPSM). We implement a prototype system over a cluster environment deployed with 56 real VM instances, and summarized valuable experience from our evaluation. As the system runs in short supply, Lightest Workload First (LWF) is mostly recommended because it can minimize the overall response extension ratio (RER) for both sequential-mode tasks and parallel-mode tasks. In a competitive situation with over-commitment of resources, the best one is combining LWF with both AAPSM and RAPSM. It outperforms other solutions in the competitive situation, by 16+% w.r.t. the worst-case response time and by 7.4+% w.r.t. the fairness.
Persistent Identifierhttp://hdl.handle.net/10722/204719

 

DC FieldValueLanguage
dc.contributor.authorDi, Sen_US
dc.contributor.authorKondo, Den_US
dc.contributor.authorWang, CLen_US
dc.date.accessioned2014-09-20T00:31:43Z-
dc.date.available2014-09-20T00:31:43Z-
dc.date.issued2015en_US
dc.identifier.citationIEEE Transactions on Computers (In press), 2015en_US
dc.identifier.urihttp://hdl.handle.net/10722/204719-
dc.description.abstractBy leveraging virtual machine (VM) technology, we optimize cloud system performance based on refined resource allocation, in processing user requests with composite services. Our contribution is three-fold. (1) We devise a VM resource allocation scheme with a minimized processing overhead for task execution. (2) We comprehensively investigate the best-suited task scheduling policy with different design parameters. (3) We also explore the best-suited resource sharing scheme with adjusted divisible resource fractions on running tasks in terms of Proportional-Share Model (PSM), which can be split into absolute mode (called AAPSM) and relative mode (RAPSM). We implement a prototype system over a cluster environment deployed with 56 real VM instances, and summarized valuable experience from our evaluation. As the system runs in short supply, Lightest Workload First (LWF) is mostly recommended because it can minimize the overall response extension ratio (RER) for both sequential-mode tasks and parallel-mode tasks. In a competitive situation with over-commitment of resources, the best one is combining LWF with both AAPSM and RAPSM. It outperforms other solutions in the competitive situation, by 16+% w.r.t. the worst-case response time and by 7.4+% w.r.t. the fairness.en_US
dc.languageengen_US
dc.publisherIEEE.en_US
dc.relation.ispartofIEEE Transactions on Computersen_US
dc.rightsIEEE Transactions on Computers. Copyright © IEEE.en_US
dc.rights©20xx IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_US
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2014 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.titleOptimization of Composite Cloud Service Processing with Virtual Machinesen_US
dc.typeArticleen_US
dc.identifier.emailDi, S: sdi@cs.hku.hken_US
dc.identifier.emailWang, CL: clwang@cs.hku.hken_US
dc.identifier.authorityWang, CL=rp00183en_US
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/TC.2014.2329685en_US
dc.identifier.hkuros239052en_US

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