Optimizing multi objective based workflow scheduling in cloud computing using black hole algorithm

F. Ebadifard, S. M. Babamir
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引用次数: 19

Abstract

Cloud computing employs parallel and distributed computing concepts to provide users with shared resources through the internet. One of the most important issues which are raised in a cloud environment is task scheduling on existing resources; so that on the one hand it can provide user's requirements, such as minimum run time or cost and on the other hand with the proper use of resources, can also cause service providers' benefits. In this paper we extended a recent heuristic algorithm called Black hole Optimization (BHO) and present a multi objective scheduling method for workflow application based on Pareto optimizer algorithm. Our proposed method can consider user requirements and also the interests of service providers. Using the balanced and unbalanced workflow we compared our proposed method with algorithms of SPEA2 and NSGA2 based on the parameters of completion time and cost and resource efficiency.
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基于黑洞算法的云计算多目标工作流调度优化
云计算采用并行和分布式计算概念,通过互联网为用户提供共享资源。在云环境中提出的最重要的问题之一是对现有资源的任务调度;这样一来,一方面可以满足用户的需求,如最小的运行时间或成本,另一方面与资源的合理利用,也可以使服务提供商受益。本文对黑洞优化算法(BHO)进行了扩展,提出了一种基于Pareto优化算法的工作流应用多目标调度方法。我们提出的方法可以考虑用户需求和服务提供商的利益。基于完成时间、成本和资源效率等参数,采用平衡和不平衡工作流与SPEA2和NSGA2算法进行了比较。
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