A game-theoretic method of fair resource allocation for cloud computing services

Wei, GY; Vasilakos, AV; Zheng, Y; Xiong, NX

dc.contributor.author	Wei, GY	en
dc.contributor.author	Vasilakos, AV	en
dc.contributor.author	Zheng, Y	en
dc.contributor.author	Xiong, NX	en
dc.date.accessioned	2014-03-01T01:32:26Z
dc.date.available	2014-03-01T01:32:26Z
dc.date.issued	2010	en
dc.identifier.issn	0920-8542	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20134
dc.subject	Cloud computing	en
dc.subject	Game theory	en
dc.subject	Resource allocation	en
dc.subject.classification	Computer Science, Hardware & Architecture	en
dc.subject.classification	Computer Science, Theory & Methods	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.other	PARALLEL	en
dc.subject.other	PREDICTION	en
dc.title	A game-theoretic method of fair resource allocation for cloud computing services	en
heal.type	journalArticle	en
heal.identifier.primary	10.1007/s11227-009-0318-1	en
heal.identifier.secondary	http://dx.doi.org/10.1007/s11227-009-0318-1	en
heal.language	English	en
heal.publicationDate	2010	en
heal.abstract	As cloud-based services become more numerous and dynamic, resource provisioning becomes more and more challenging. A QoS constrained resource allocation problem is considered in this paper, in which service demanders intend to solve sophisticated parallel computing problem by requesting the usage of resources across a cloud-based network, and a cost of each computational service depends on the amount of computation. Game theory is used to solve the problem of resource allocation. A practical approximated solution with the following two steps is proposed. First, each participant solves its optimal problem independently, without consideration of the multiplexing of resource assignments. A Binary Integer Programming method is proposed to solve the independent optimization. Second, an evolutionary mechanism is designed, which changes multiplexed strategies of the initial optimal solutions of different participants with minimizing their efficiency losses. The algorithms in the evolutionary mechanism take both optimization and fairness into account. It is demonstrated that Nash equilibrium always exists if the resource allocation game has feasible solutions.	en
heal.publisher	SPRINGER	en
heal.journalName	JOURNAL OF SUPERCOMPUTING	en
dc.identifier.doi	10.1007/s11227-009-0318-1	en
dc.identifier.isi	ISI:000282225700007	en
dc.identifier.volume	54	en
dc.identifier.issue	2	en
dc.identifier.spage	252	en
dc.identifier.epage	269	en