Simulating peer-to-peer cloud resource scheduling

dc.authoridErdil, D. Cenk/0000-0003-1380-3497
dc.authorwosidErdil, D. Cenk/ABE-8301-2020
dc.contributor.authorErdil, D. Cenk
dc.date.accessioned2024-07-18T20:42:20Z
dc.date.available2024-07-18T20:42:20Z
dc.date.issued2012
dc.departmentİstanbul Bilgi Üniversitesien_US
dc.description.abstractResource scheduling in large-scale distributed systems, such as grids and clouds, is difficult due to the size, dynamism, and volatility of resources. These resources are eclectic and autonomous, and may exhibit different usage policies, levels of participation, capabilities, local load, and reliability. Moreover, applications are likely to exhibit various patterns and levels, and distributed resources may organize into various different overlay topologies for information and query dissemination. Researchers have proposed a wide variety of approaches and policies for mapping offered load onto resources and for solving the various component parts of the scheduling problem. However, production clouds and grids may be underutilized, and may not exhibit the load to effectively characterize all of the scheduling system inputs. The composition of large-scale systems is also changing, potentially to include more individual and peer-to-peer resources. These factors will influence the effectiveness of proposed scheduling solutions. Therefore, a simulation environment is necessary to study different approaches under different scenarios, especially those that are expected, but that are not currently characteristic of existing systems. This article describes a general-purpose peer-to-peer simulation environment that allows a wide variety of parameters, protocols, strategies and policies to be varied and studied. To provide a proof of concept, utilization of the simulation environment is presented in a large-scale distributed system problem that includes a core model and related mechanisms. In particular, this article presents a definition and possible peer-to-peer solutions for the large-scale scheduling problem. Moreover, this article describes a general simulation model, some policies that can be varied, an implementation, and some sample results.en_US
dc.identifier.doi10.1007/s12083-011-0112-8
dc.identifier.endpage230en_US
dc.identifier.issn1936-6442
dc.identifier.issn1936-6450
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-84858618691en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage219en_US
dc.identifier.urihttps://doi.org/10.1007/s12083-011-0112-8
dc.identifier.urihttps://hdl.handle.net/11411/7248
dc.identifier.volume5en_US
dc.identifier.wosWOS:000301869900002en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofPeer-To-Peer Networking and Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectPeer-To-Peer Schedulingen_US
dc.subjectCloud Resource Schedulingen_US
dc.subjectAdaptive Dissemination Protocolsen_US
dc.subjectCloud Simulation And Modelingen_US
dc.subjectHybrid Cloud Modelingen_US
dc.titleSimulating peer-to-peer cloud resource scheduling
dc.typeArticle

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