2010
DOI: 10.1016/j.future.2009.08.003
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Dynamic resource selection heuristics for a non-reserved bidding-based Grid environment

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Cited by 30 publications
(25 citation statements)
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“…Wang et al [28] proposed a dynamic resource selection heuristic for a non-reserved bidding-based grid environment, wherein a set of deterministic and probabilistic resource selection heuristics are evaluated to minimize the job turnaround time in online systems. Five basic heuristics and various levels of information released by resource providers are considered to yield the corresponding variants under different scenarios.…”
Section: Related Workmentioning
confidence: 99%
“…Wang et al [28] proposed a dynamic resource selection heuristic for a non-reserved bidding-based grid environment, wherein a set of deterministic and probabilistic resource selection heuristics are evaluated to minimize the job turnaround time in online systems. Five basic heuristics and various levels of information released by resource providers are considered to yield the corresponding variants under different scenarios.…”
Section: Related Workmentioning
confidence: 99%
“…The ORT aims to optimize mean response time for non-real-time tasks, and the OMR is to achieve the optimized mean deadline-miss rate for soft realtime tasks. To evaluate the performance of various co-allocation policies, the researchers conduct extensive experiments in large-scale grid testbed DAS-2 [10][11][12]23]. Based on their experimental results, they draw an important conclusion that workload-aware co-allocation policies are more effective to reduce the mean response time and obtain better load-balance.…”
Section: Related Workmentioning
confidence: 99%
“…Therefore, resource co-allocation is always the key issue in grid systems [2,3]. At present, studies on co-allocation mainly focus on co-allocation framework [2][3][4][5][6] and co-allocation policy [7][8][9][10][11][12]. With the development of grid middleware, many effective co-allocation frameworks have be developed and deployed in practical grid systems.…”
Section: Introductionmentioning
confidence: 99%
“…The raise in numbers of resources and the regularity of task demands generate overload problems hence the matchmaking methods might lead the matchmaker to performance problems [13]. Furthermore the matchmaker information often are out of dates, this is because the status of resources changes frequently and the matchmaker does not learn about the resources status until the resources advertise their new status to the matchmaker [13][14][15].The matchmaker can be implemented by job manager [16] or by using centralized resource broker as discussed in [8].…”
Section: Resource Selection Models: 31matchmaking Modelmentioning
confidence: 99%