Social ranking criteria for pairwise gossiping in large-scale resource scheduling

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dc.authorscopusid21742287100
dc.contributor.authorErdil, D.C.
dc.date.accessioned2024-07-18T20:17:04Z
dc.date.available2024-07-18T20:17:04Z
dc.date.issued2011
dc.descriptionBahcesehir University;Grid Telekom;HUAWEI Technologies Co., Ltd.;IBM Turkey;IEEE Turkey Sectionen_US
dc.description2011 International Conference on High Performance Computing and Simulation, HPCS 2011 -- 4 July 2011 through 8 July 2011 -- Istanbul -- 86619en_US
dc.description.abstractThe concept of online presence has long been available only to people with enough technical background to complete a set of tasks with gory details. Thus, actual utilization of large-scale networks, such as grids and clouds, has not been realized until recently. With the advances in technology in multiple areas, such as multi-core CPUs, low-power energy-efficient FPGAs, virtualization, service-oriented architectures and web services, and autonomic computing, there has been an area of opportunity for the not-so-technologically advanced masses to actually take part in large-scale computing. Social networks are important to large-scale networking because they close one of the fundamental gaps: the trust between autonomous entities, which usually do not have a relationship history, or a ranking mechanism. One other common problem in large-scale networking is resource matchmaking, finding the right set of resource providers for a set of requesters, and vice versa. Traditional approaches to resource matchmaking use centralized repositories, which at the minimum does not scale well, among other issues. In this study, we propose adaptive pairwise gossiping protocols to take feedback from the system, based on existing basic social relationships, and trust levels between autonomous entities in the network. In addition to the ranking criteria we previously employed while selecting which nodes to gossip to, such as execution history, average distance, freshness of information, we also propose employing several social ranking criteria: overall popularity, trusted execution history, and social distance. By simulation, we show that (i) these social ranking criteria can be mapped to traditional ranking criteria in large-scale resource matchmaking, and (ii) the social ranking criteria perform comparably, based on several performance metrics. Moreover, we have a prototype social networking application that can incorporate such ranking criteria. We are still in the implementation phase, in which we are working on particular methodologies to measure and compare the performances of the two similar sets of ranking criteria in two different domains. © 2011 IEEE.en_US
dc.identifier.doi10.1109/HPCSim.2011.5999895
dc.identifier.endpage706en_US
dc.identifier.isbn9781612843810
dc.identifier.scopus2-s2.0-80053002621en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage699en_US
dc.identifier.urihttps://doi.org/10.1109/HPCSim.2011.5999895
dc.identifier.urihttps://hdl.handle.net/11411/6399
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.relation.ispartofProceedings of the 2011 International Conference on High Performance Computing and Simulation, HPCS 2011en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectLarge-Scale Resource Schedulingen_US
dc.subjectPairwise Gossiping Protocolsen_US
dc.subjectSocial Ranking Criteriaen_US
dc.subjectAutonomic Computingen_US
dc.subjectAutonomous Entitiesen_US
dc.subjectAverage Distanceen_US
dc.subjectCommon Problemsen_US
dc.subjectDifferent Domainsen_US
dc.subjectEnergy Efficienten_US
dc.subjectExecution Historyen_US
dc.subjectFundamental Gapsen_US
dc.subjectGossiping Protocolsen_US
dc.subjectLarge-Scale Computingen_US
dc.subjectLarge-Scale Networken_US
dc.subjectLow Poweren_US
dc.subjectMulti Coreen_US
dc.subjectMultiple Areasen_US
dc.subjectPerformance Metricsen_US
dc.subjectResource Providersen_US
dc.subjectResource-Schedulingen_US
dc.subjectService Orienteden_US
dc.subjectSocial Distanceen_US
dc.subjectSocial Networksen_US
dc.subjectSocial Ranking Criteriaen_US
dc.subjectSocial Relationshipsen_US
dc.subjectTechnical Backgrounden_US
dc.subjectTrust Levelen_US
dc.subjectVirtualizationsen_US
dc.subjectComputer Software Selection And Evaluationen_US
dc.subjectComputer Supported Cooperative Worken_US
dc.subjectEnergy Efficiencyen_US
dc.subjectInformation Servicesen_US
dc.subjectInternet Protocolsen_US
dc.subjectProgram Processorsen_US
dc.subjectSchedulingen_US
dc.subjectWeb Servicesen_US
dc.subjectService Oriented Architecture (Soa)en_US
dc.titleSocial ranking criteria for pairwise gossiping in large-scale resource scheduling
dc.typeConference Object

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