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dc.creatorKoutsopoulos, I.en
dc.creatorTassiulas, L.en
dc.creatorGkatzikis, L.en
dc.date.accessioned2015-11-23T10:36:52Z
dc.date.available2015-11-23T10:36:52Z
dc.date.issued2009
dc.identifier10.1109/IWQoS.2009.5201412
dc.identifier.isbn9781424438761
dc.identifier.issn1548615X
dc.identifier.urihttp://hdl.handle.net/11615/29986
dc.description.abstractWe consider a content sharing network of noncooperative peers. The strategy set of each peer comprises, (i) client strategies, namely feasible request load splits to servers, and (ii) server strategies, namely scheduling disciplines on requests. First, we consider the request load splitting game for given server strategies such as First-In-First-Out or given absolute priority policies. A peer splits its request load to servers to optimize its performance objective. We consider the class of best response load splitting policies residing between the following extremes: a truly selfish, or egotistic one, where a peer optimizes its own delay, and a pseudo-selfish or altruistic one, where a peer also considers incurred delays to others. We derive conditions for Nash equilibrium points (NEPs) and discuss convergence to NEP and properties of the NEP. For both the egotistic cases, the NEP is unique. For the altruistic case, each of the multiple NEPs is an optimum, a global one for the FIFO case and a local one otherwise. Next, we include scheduling in peer strategies. With its scheduling discipline, a peer cannot directly affect its delay, but it can affect the NEP after peers play the load splitting game. The idea is that peer i should offer high priority to (and thus attract traffic from) higher-priority peers that cause large delay to i at other servers. We devise two-stage game models, where, at a first stage, a peer selects a scheduling rule in terms of a convex combination of absolute priorities, and subsequently peers play the load splitting game. In the most sophisticated rule, a peer selects a scheduling discipline that minimizes its delay at equilibrium, after peers play the load splitting game. We also suggest various heuristics for picking the scheduling discipline. Our models and results capture the dual client-server peer role and aim at quantifying the impact of selfish peer interaction on equilibria. ©2009 IEEE.en
dc.source.urihttp://www.scopus.com/inward/record.url?eid=2-s2.0-70449572509&partnerID=40&md5=7f607e1b54035a51da850749660c8d2d
dc.subjectBest responseen
dc.subjectClient serveren
dc.subjectContent Sharingen
dc.subjectConvex combinationsen
dc.subjectFirst-in-first-outen
dc.subjectLarge delaysen
dc.subjectNash equilibrium pointen
dc.subjectPeer interactionsen
dc.subjectPeer rolesen
dc.subjectPeer-to-Peer networksen
dc.subjectPerformance objectiveen
dc.subjectScheduling disciplineen
dc.subjectScheduling rulesen
dc.subjectTwo stageen
dc.subjectAd hoc networksen
dc.subjectDistributed computer systemsen
dc.subjectQuality controlen
dc.subjectQuality of serviceen
dc.subjectSchedulingen
dc.subjectTelecommunication networksen
dc.subjectServersen
dc.titleClient and server games in peer-to-peer networksen
dc.typeconferenceItemen


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