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OPT-Min-Min Scheduling Algorithm of Grid Resources

机译:电网资源的选择光敏调度算法

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As a newly emerged distributed computing platform, the Gird aims at the implementation of resources sharing and collaborative computing on the internet. Research on grid resource scheduling algorithm is one of the core problems of grid technology, as well as an essential part of grid resource management. Resource scheduling in grid environment refers to the application of tasks scheduling algorithm to assign the works in the grid to the right resources. During the allocation process, the computing performance of grid resource nodes, communication parameters and loading balance, etc., shall be put into consideration. Since they are all dynamic for both the grid resources and the grid resource nodes, requirements on grid resource scheduling algorithm are relatively higher if compared to those existing parallel resource scheduling algorithm. Based on the Min-Min scheduling algorithm, the OPTMin- Min scheduling algorithm is presented to overcome the drawbacks. Upon the basis of applying Min-Min prescheduling into stage one, by adapting the strategy of tworounds scheduling, the assignment on heavy load resources are rescheduled to balance the load. Actual cases are used to illustrate the superiority of OPT-Min-Min scheduling algorithm to the Min-Min scheduling algorithm. Simulation experiments were carried out to the batch grid resource scheduling algorithms including Min-Min, Max-Min, Minmean and OPT-Min-Min. According to the ETC generation technique used in experimental benchmarks, ETC matrix was generated. By the comparing and analyzing the Min- Min, Max-Min and Min-mean scheduling algorithm, the validity of OPT-Min-Min scheduling algorithm is proved.
机译:作为一个新出现的分布式计算平台,Gird旨在在互联网上实施资源共享和协作计算。网格资源调度算法研究是电网技术的核心问题之一,以及网格资源管理的重要组成部分。网格环境中的资源调度是指任务调度算法的应用将网格中的作品分配给右权资源。在分配过程中,应考虑网格资源节点,通信参数和加载平衡等的计算性能。由于它们都是动态的网格资源和网格资源节点,因此如果与现有的并行资源调度算法相比,网格资源调度算法的要求相对较高。基于MIN-MIN调度算法,提出了optmin- Min调度算法来克服缺点。在将Min-min预先定期应用于阶段的基础上,通过调整Twordounds调度的策略,重新安排重载资源的分配以平衡负载。实际情况用于说明Phy-Min调度算法到Min-Min调度算法的优越性。仿真实验是对批量网格资源调度算法进行,包括MIN-MIN,MAX-MIN,MINEMEN和OPT-MIN。根据在实验基准中使用的等生成技术,生成等等。通过比较和分析Min-Min,MAX-MIN和最小均值调度算法,证明了Opt-Min-Min调度算法的有效性。

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