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用爬山法实现无中心式网格调度 被引量:1

Implementation of de-centralized grid scheduling using hill climbing
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摘要 为方便网格资源的扩展,网格调度应当是无中心的。为在尽可能多的计算资源中为单地点作业优化资源选择,这里采用了爬山算法。当一个网格调度器收到一个单地点作业,爬山法被激活,根据网格调度器之间的相邻关系为作业找出最适合的计算系统,这里每个计算系统的适合度用预测的作业响应时间表示。实验模拟了无中心式网格调度与计算系统之间的性能差别,每个计算系统的本地调度采用保守式装填法,网格工作负荷由模型得到,并用一段工作负荷的平均响应时间衡量调度性能。实验结果表明,即使在作业提交点分布不均匀且运行时间估计不准确情况下,爬山法仍可有效改善单地点作业的调度。 To facilitate the expansion of grid resources, grid scheduling is de-centralized. To optimize the resource selection of each single-site job in as many resources as possible, hill climbing is applied. When a grid scheduler receives a single-site job, hill climbing is triggered to find the most appropriate computing system for the job based on the neighbor relations between grid schedulers, where the appropriateness degree of one computing system for the job is represented by the predicted job response time on the computing system. In experiments, the de-centralized grid scheduling and performance differences of computing systems are simulated respectively, and conservative backfilling is used as the local scheduling strategy on each computing system. The grid workload is obtained by modeling, while the average job response time of one segment of workload is used to represent scheduling performance. Results show hill climbing is efficient to improve the schedules of single-site jobs, even when the distribution ofjob submittal location is non-uniform or the runtime estimates are inaccurate.
作者 张琳 黄仙姣
出处 《计算机工程与设计》 CSCD 北大核心 2006年第11期2073-2076,共4页 Computer Engineering and Design
关键词 网格 无中心式网格调度 平均响应时间 爬山法 grid de-centralized grid scheduling average response time hill climbing
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  • 1Di Martino V.Sub optimal scheduling in a grid using genetic algorithms[A].International Parallel and Distributed Processing Symposium (IPDPS'03)[C].2003.148-154.
  • 2Ernemann C,Hamscher V,Schwiegelshohn U,et al.On advantages of grid computing for parallel job scheduling[A].2nd IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGRID2002)[C].2002.31-38
  • 3Ranganathan K,Foster I.Decoupling computation and data scheduling in distributed data-intensive applications[A].11th IEEE International Symposium on High Performance Distributed Computing[C].2002.352-258.
  • 4Subramani V,Kettimuthu R,Srinivasan S,et al.Distributed job dcheduling on computatinal grids using multiple simultaneous requests[A].11th IEEE International Symposium on High Performance Distributed Computing[C].2002.359-366.
  • 5Hongtu Chen,Muthucumaru Maheswaran.Distributed dynamic scheduling of compocomputing system tasks on grid computing systems[A].16th International Parallel and Distributed Processing Symposium (IPDPS'02)[C].2002.88-97.
  • 6Arora M,Das S K,Biswas R.A de-centralized scheduling and load balancing algorithm for heterogeneous grid environments[A].2002 International Conference on Parallel Processing Workshops[C].2002.499-505.
  • 7Junwei Cao,Spooner D P,Jarvis S A,et al.Agent-based grid load balancing using performance-driven task scheduling[A].International Parallel and Distributed Processing Symposium (IPDPS'03)[C].2003.49-58.
  • 8Mu'alem A W,Feitelson D G.Utilization,predictability,workloads,and user runtime estimates in scheduling the IBM SP2 with backfilling.Parallel and Distributed Systems[J].IEEE Transactions,2001,12(6):529 -543.
  • 9Windisch K,Lo V,Feitelson D,et al.A comparison of workload traces from two production parallel machines[A].6th Symposium on the Frontiers of Massively Parallel Computation[C].Annapolis,MD,USA,1996.319-326.
  • 10Feitelson D.Workload modeling for performance evaluation[EB/OL].2003.http://citeseer.nj.nec.com/531320.html.

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