Global dynamic load-balancing for decentralised distributed simulation

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dc.contributor.authorBragard, Quentin-
dc.contributor.authorVentresque, Anthony-
dc.contributor.authorMurphy, Liam, B.E.- IEEEen
dc.description2014 Winter Simulation Conference (WSC), Savanah, Georgia, USA, 7 - 10 December, 2014en
dc.description.abstractDistributed simulations require partitioning mechanisms to operate, and the best partitioning algorithms try to load-balance the partitions. Dynamic load-balancing, i.e. re-partitioning simulation environments at run-time, becomes essential when the load in the partitions change. In decentralised distributed simulation the information needed to dynamically load-balance seems difficult to collect and to our knowledge, all solutions apply a local dynamic load balancing: partitions exchange load only with their neighbours (more loaded partitions to less loaded ones). This limits the effect of the load-balancing. In this paper, we present a global dynamic load-balancing of decentralised distributed simulations. Our algorithm collects information in a decentralised fashion and makes re-balancing decisions based on the load processed by every logical processes. While our algorithm has similar results to others in most cases, we show an improvement of the load-balancing up to 30% in some challenging scenarios against only 12.5% for a local dynamic load-balancing.en
dc.description.sponsorshipScience Foundation Irelanden
dc.publisherInstitute of Electrical and Electronic Engineers (IEEE)en
dc.rights© © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en
dc.subjectLoad balancingen
dc.subjectBehaviour simulationen
dc.subjectDynamic partitioningen
dc.titleGlobal dynamic load-balancing for decentralised distributed simulationen
dc.typeConference Publicationen
dc.statusPeer revieweden
dc.neeo.contributorMurphy|Liam, B.E.|aut|-
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