Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/1696

TitleScheduling under conditions of uncertainty: a bayesian approach
Author(s)Santos, Luís Paulo
Proença, Alberto José
KeywordsScheduling
Bayesian Networks
Parallel Computing
Issue dateAug-2004
PublisherSpringer-Verlag Berlin
JournalLecture Notes in Computer Science
Citation[DANELUTTO Marco; VANNESSCHI Marco; LAFORENZA Domenico, ed. lit. - "Euro-Par 2004 Parallel : proceedings of the International Euro-Par Conference, 10, Italy, 2004". [S.l] : Springer, 2004. ISBN 3-540-22924-8.]
Abstract(s)The efficient execution of irregular parallel applications on shared distributed systems requires novel approaches to scheduling, since both the application requirements and the system resources exhibit an unpredictable behavior. This paper proposes Bayesian decision networks as the paradigm to handle the uncertainty a scheduler has about the environment's current and future states. Experiments performed with a parallel ray tracer show promising performance improvements over a deterministic approach of identical complexity. These improvements grow as the level of system sharing and the application's workload irregularity increase, suggesting that the effectiveness of decision network based schedulers grows with the complexity of the environment being managed.
TypeBook part
URIhttp://hdl.handle.net/1822/1696
ISBN3540229248
ISSN0302-9743
Peer-Reviewedyes
AccessOpen access
Appears in Collections:DI/CCTC - Artigos (papers)

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