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Live Migration for Multiple Correlated Virtual Machines in Cloud-based Data Centers

dc.contributor.authorSun, Gang
dc.contributor.authorLiao, Dan
dc.contributor.authorZhao, Dongcheng
dc.contributor.authorXu, Zichuan
dc.contributor.authorYu, Hongfang
dc.date.accessioned2020-01-06T03:48:19Z
dc.date.issued2015
dc.date.updated2019-08-11T08:17:04Z
dc.description.abstractWith the development of cloud computing, virtual machine migration is emerging as a promising technique to save energy, enhance resource utilizations, and guarantee Quality of Service (QoS) in cloud datacenters. Most of existing studies on the virtual machine migration, however are based on a single virtual machine migration. Although there are some researches on multiple virtual machines migration, the author usually does not consider the correlation among these virtual machines. In practice, in order to save energy and maintain system performance, cloud providers usually need to migrate multiple correlated virtual machines or migrate the entire virtual datacenter (VDC) request. In this paper, we focus on the efficient online live migration of multiple correlated VMs in VDC requests, for optimizing the migration performance. To solve this problem, we propose an efficient VDC migration algorithm (VDC-M). We use the US-wide NSF network as substrate network to conduct extensive simulation experiments. Simulation results show that the performance of the proposed algorithm is promising in terms of the total VDC remapping cost, the blocking ratio, the average migration time and the average downtime.en_AU
dc.description.sponsorshipThis research is partially supported by the National Grand Fundamental Research 973 Program of China under grant (2013CB329103), Natural Science Foundation of China grant (61271171, 61571098), China Postdoctoral Science Foundation (2015M570778), the Fundamental Research Funds for the Central Universities (ZYGX2013J002), Guangdong Science and Technology Project (2012B090400031, 2012B090500003, 2012B091000163), and National Development and Reform Commission Project.en_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn1939-1374en_AU
dc.identifier.urihttp://hdl.handle.net/1885/196524
dc.language.isoen_AUen_AU
dc.publisherIEEE Computer Societyen_AU
dc.rights© 2015 IEEEen_AU
dc.sourceIEEE Transactions on Services Computingen_AU
dc.titleLive Migration for Multiple Correlated Virtual Machines in Cloud-based Data Centersen_AU
dc.typeJournal articleen_AU
local.bibliographicCitation.lastpage14en_AU
local.bibliographicCitation.startpage1en_AU
local.contributor.affiliationSun, Gang, University of Electronic Science and Technology of Chinaen_AU
local.contributor.affiliationLiao, Dan, University of Electronic Science and Technology of Chinaen_AU
local.contributor.affiliationZhao, Dongcheng, University of Electronic Science and Technology of Chinaen_AU
local.contributor.affiliationXu, Zichuan (Edward), College of Engineering and Computer Science, ANUen_AU
local.contributor.affiliationYu, Hongfang, University of Electronic Science and Technology of Chinaen_AU
local.contributor.authoruidXu, Zichuan (Edward), u4990040en_AU
local.description.embargo2037-12-31
local.description.notesImported from ARIESen_AU
local.identifier.absfor080505 - Web Technologies (excl. Web Search)en_AU
local.identifier.absseo970108 - Expanding Knowledge in the Information and Computing Sciencesen_AU
local.identifier.ariespublicationu4056230xPUB574en_AU
local.identifier.doi10.1109/TSC.2015.2477825en_AU
local.identifier.scopusID2-s2.0-84948687789
local.identifier.thomsonID000429798800006
local.publisher.urlhttps://www.ieee.org/en_AU
local.type.statusPublished Versionen_AU

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