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A Heuristic Algorithm for Task Scheduling Based on Mean Load on Grid

ISSN号：1000-9000
期刊名称：《计算机科学技术学报：英文版》
时间：0
分类：TP31[自动化与计算机技术—计算机软件与理论;自动化与计算机技术—计算机科学与技术]
作者机构：[1]Department of Computer Science, Tongji University, Shanghai 200092, P.R. China, [2]College of Information Science & Engineering, Shandong University of Science & Technology, Qingdao 266510, P.R. China
相关基金：This work is supported by the National Natural Science Foundation of China （Grant Nos. 90412013, 60473094 and 60534060）, the National Basic Research 973 Program of China （Grant Nos. 2003CB316902 and 2004CB318001-03）, and the Shanghai Science ＆： Technology Research Plan （Grant Nos. 04XD14016 and 05DZ15004）.

关键词：启发式算法, 任务调度, 负载平衡, 网格, heuristic algorithm, task scheduling, load balancing, knowledge grid

中文摘要：

有效任务安排对在格子计算环境上完成高效批评。在格子上安排的任务在这 paper.A 作为优化问题被学习令人满意的资源装载在格子环境上平衡的启发式的任务调度算法被介绍。由采用平均数的算法时间表任务作为试探信息基于任务装载预兆的执行时间获得起始的调度策略。然后，最佳调度策略被选择二台机器完成经由再分配他们的任务在下面改变他们的负担的令人满意的状况他们的吝啬的负担启发式。选择机器和任务的方法在这篇论文被给增加系统的产量并且减少全部的等待时间。算法的效率被分析，建议算法的表演经由广泛的模拟实验被评估。试验性的结果证明试探算法显著地表现高保证负担平衡并且完成最佳调度策略几乎所有时间。而且，结果证明我们的算法以时间复杂性是高有效的。

英文摘要：

Efficient task scheduling is critical to achieving high performance on grid computing environment. The task scheduling on grid is studied as optimization problem in this paper. A heuristic task scheduling algorithm satisfying resources load balancing on grid environment is presented. The algorithm schedules tasks by employing mean load based on task predictive execution time as heuristic information to obtain an initial scheduling strategy. Then an optimal scheduling strategy is achieved by selecting two machines satisfying condition to change their loads via reassigning their tasks under the heuristic of their mean load. Methods of selecting machines and tasks are given in this paper to increase the throughput of the system and reduce the total waiting time. The efficiency of the algorithm is analyzed and the performance of the proposed algorithm is evaluated via extensive simulation experiments. Experimental results show that the heuristic algorithm performs significantly to ensure high load balancing and achieve an optimal scheduling strategy almost all the time. Furthermore, results show that our algorithm is high efficient in terms of time complexity.

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