A List-based Heuristic Algorithm for Static Task Scheduling in Heterogeneous Distributed Computing Systems

Hadi Gholami, Reza Zakerian
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引用次数: 6

Abstract

Executing complicated computations in parallel increases the speed of computing and brings user delight to the system. Decomposing the program into several small programs and running multiple parallel processors are modeled by Directed Acyclic Graph. Scheduling nodes to execute this task graph is an important problem that will speed up computations. Since task scheduling in this graph belongs to NP-hard problems, various algorithms were developed for node scheduling to contribute to quality service delivery. The present study brought a heuristic algorithm named looking ahead sequencing algorithm (LASA) to cope with static scheduling in heterogeneous distributed computing systems with the intention of minimizing the schedule length of the user application. In the algorithm proposed here, looking ahead is considered as a criterion for prioritizing tasks. Also, a property called Emphasized Processor has been added to the algorithm to emphasize the task execution on a particular processor. The effectiveness of the algorithm was shown on few workflow type applications and the results of the algorithm implementation were compared with two more heuristic and meta-heuristic algorithms.
异构分布式计算系统中静态任务调度的启发式算法
并行执行复杂的计算提高了计算速度,给系统带来了用户乐趣。采用有向无环图的方法将程序分解成若干小程序,并运行多个并行处理器。调度节点来执行这个任务图是一个重要的问题,它将加快计算速度。由于该图中的任务调度属于np困难问题,因此开发了各种用于节点调度的算法,以促进高质量的服务交付。针对异构分布式计算系统中的静态调度问题,提出了一种启发式算法——前瞻排序算法(LASA),以最小化用户应用程序的调度长度。在本文提出的算法中,前瞻性被视为任务优先级排序的标准。此外,还向算法中添加了一个称为强调处理器的属性,以强调在特定处理器上执行任务。在几种工作流类型的应用中证明了该算法的有效性,并将算法的实现结果与两种启发式和元启发式算法进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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