Two Level Job-Scheduling Strategies for a Computational Grid

Tchernykh, Andrei; Ramírez, Juan Manuel Covarrubias; Avetisyan, Arutyun; Kuzjurin, N. N.; Грушин, Д. А.; Zhuk, Sergey

doi:10.1007/11752578_93

Cited by 33 publications

(19 citation statements)

References 12 publications

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“…Even more, the next example shows that already in the concurrent-submission case, list scheduling cannot guarantee a constant bound for Cmax C * max for all problem instances. Note that a similar example has already been presented by Tchernykh et al [12]. jobs.…”

Section: List Schedulingsupporting

confidence: 74%

“…They claim that the makespan objective is not applicable and propose a different criterion based on total processor cycle consumption. Tchernykh et al [12] address the performance of various 2-stage algorithms with respect to the makespan objective. Their model is similar to our model as explained in Section 2.…”

Section: Introductionmentioning

confidence: 99%

“…We should only address both properties in a single model once we have understood models with a single property well enough. Processor heterogeneity is already subject of the classic machine models Q m and R m [8] while only Tchernykh et al [12] provide some results for the separate parallel identical machine model. Therefore, the focus of this paper is on this property of Grids.…”

Section: Introductionmentioning

confidence: 99%

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Online scheduling in grids

Schwiegelshohn

Tchernykh

Yahyapour

2008

2008 IEEE International Symposium on Parallel and Distributed Processing

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Section: List Schedulingsupporting

confidence: 74%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Online scheduling in grids

Schwiegelshohn

Tchernykh

Yahyapour

2008

2008 IEEE International Symposium on Parallel and Distributed Processing

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“…Their idea is to submit each job to multiple sites, and cancel redundant submissions when one of the sites is able to start the job. In [33] they concentrate on two-level hierarchy scheduling: at the first level broker allocates computational jobs to parallel computers. At the second level each computer generates schedules of the parallel jobs assigned to it by its own local scheduler.…”

Section: Related Workmentioning

confidence: 99%

A comparison of utility-oriented algorithms for scheduling parallel tasks in multi-cluster grid

Zhang

Luo

2009

Cluster Comput

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Scheduling parallel tasks in multi-cluster grid can be seen as two interdependent problems: cluster allocation and scheduling parallel task on the allocated cluster. In this paper both rigid and moldable parallel tasks are considered. We propose a theoretical model of utility-oriented parallel task scheduling in multi-cluster grid with advance reservations. On the basis of the model we present an approximation algorithm, a repair strategy based genetic algorithm and greedy heuristics MaxMax, T-Sufferage and R-Sufferage to solve the two interdependent problems. We compare the performance of these algorithms in aspect of utility optimality and timing results. Simulation results show on average the (1 + α)-approximation algorithm achieves the best tradeoff between utility optimality and timing. Genetic algorithm could achieve better utility than greedy heuristics and approximate algorithm at expensive time cost. Greedy heuristics do not perform equally well when adapted to different utility functions while the approximation algorithm shows its intrinsic stable performance.

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“…These algorithms are applied dominantly at two levels: grid-and cluster-level. Scheduling policies covering and combining both of these levels are listed in [3][4][5] and references therein. In addition, some algorithms are implemented with regard to the knowledge about characteristics of jobs.…”

Section: Introductionmentioning

confidence: 99%

A generalized model for investigating scheduling schemes in computational clusters

Tran

et al. 2013

Simulation Modelling Practice and Theory

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In this paper, we present a generalized model for the performance evaluation of scheduling compute-intensive jobs with unknown service times in computational clusters. We propose the application of parameters defined in the SPECpower ssj2008 benchmark of the Standard Performance Evaluation Corporation to construct a performance evaluation model. In addition, we also define a method to rank physical servers based on either the high performance priority or the energy efficiency priority, and measures to characterize the performance of computational clusters.We investigate three schemes (separate queue, class queue and common queue) for buffering jobs in a computational cluster that is built from Commercial OffThe-Shelf (COTS) servers. Numerical results show that the buffering schemes do not have impact on performance measures related to the energy consumption of the investigated cluster. However, the buffering schemes play an important role in the quality of service parameters such the waiting time and the response time experienced by arriving jobs. Furthermore, Dynamic Voltage and Frequency Scaling should be carefully applied if one wants to reduce the energy consumption of computational clusters.

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Two Level Job-Scheduling Strategies for a Computational Grid

Cited by 33 publications

References 12 publications

Online scheduling in grids

Online scheduling in grids

A comparison of utility-oriented algorithms for scheduling parallel tasks in multi-cluster grid

A generalized model for investigating scheduling schemes in computational clusters

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