Standard deviation of probability of processor availability based task scheduling algorithm

Vijayalakshmi A. Lepakshi, C. Prashanth
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引用次数: 0

Abstract

Cloud [2] is an interconnection of clusters of different heterogeneous processors that provides different services such as SaaS, PaaS, IaaS etc., to different users. User's jobs are diverse and have different requirements. Jobs can be represented as Directed Acyclic Graphs and scheduling these jobs is a known NP-Complete problem. There are many heuristics developed earlier for job scheduling, that work differently in different environments with different requirements. A new heuristic SDPA, using Standard Deviation of probability of resource availability is developed for scheduling tasks which reduces makespan. It works in two stages. During first stage jobs are arranged based on the upward ranks and during the second stage jobs are allotted to the processor based on the standard deviation of probability of processor availability. Performance metrics such as Speedup, SLR and makespan are used to compare the performance of the new heuristic with existing one.
基于处理器可用性概率标准差的任务调度算法
云[2]是由不同的异构处理器组成的集群的互连,这些处理器为不同的用户提供不同的服务,如SaaS、PaaS、IaaS等。用户的工作是多种多样的,有不同的要求。作业可以表示为有向无环图,调度这些作业是一个已知的np完全问题。早前针对作业调度开发了许多启发式方法,它们在不同环境、不同需求下的工作方式也不同。提出了一种新的启发式SDPA方法,利用资源可用性概率的标准差来减少完工时间。它分为两个阶段。在第一阶段,作业按照向上排列,在第二阶段,作业按照处理器可用性概率的标准差分配给处理器。性能指标,如加速,单反和最长时间被用来比较新的启发式的性能与现有的。
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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