A multi-objective task scheduling algorithm for heterogeneous multi-cloud environment

S. K. Panda, P. K. Jana
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引用次数: 71

Abstract

Cloud Computing has become a popular computing paradigm which has gained enormous attention in delivering on-demand services. Task scheduling in cloud computing is an important issue that has been well researched and many algorithms have been developed for the same. However, the goal of most of these algorithms is to minimize the overall completion time (i.e., makespan) without looking into minimization of the overall cost of the service (referred as budget). Moreover, many of them are applicable to single-cloud environment. In this paper, we propose a multi-objective task scheduling algorithm for heterogeneous multi-cloud environment which takes care both these issues. We perform rigorous experiments on some synthetic and benchmark data sets. The experimental results show that the proposed algorithm balances both the makespan and total cost in contrast to two existing task scheduling algorithms in terms of various performance metrics including makespan, total cost and average cloud utilization.
异构多云环境下的多目标任务调度算法
云计算已经成为一种流行的计算范式,它在提供按需服务方面获得了极大的关注。任务调度是云计算中的一个重要问题,已经得到了很好的研究,并开发了许多算法。然而,大多数这些算法的目标是最小化总体完成时间(即makespan),而不考虑最小化服务的总体成本(称为预算)。而且,其中很多都适用于单云环境。本文提出了一种异构多云环境下兼顾这两个问题的多目标任务调度算法。我们在一些合成和基准数据集上进行了严格的实验。实验结果表明,与现有的两种任务调度算法相比,该算法在最大时间跨度、总成本和平均云利用率等性能指标上平衡了最大时间跨度和总成本。
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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