云计算环境下基于负载均衡的任务调度优化算法

Shibiao Mu
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引用次数: 1

摘要

为了在云计算平台中实现负载均衡约束下的最优任务调度方案。我们利用CloudSim模拟器构建云计算环境,CloudSim包含三个组件:1)CloudSim核心仿真引擎;2) CloudSim基本结构;3)用户代码。在此基础上,提出了一种基于遗传算法的面向负载均衡的任务调度优化算法,并通过分析染色体的基因值获得任务分配结果。为了保证遗传算法的收敛速度,我们将计算时间和计算代价综合起来设计适应度函数。此外,我们还设计了自适应交叉和变异操作,以提高搜索效率。最后,通过实验验证了所提算法的性能。实验结果表明,该算法能够以较低的计算时间和成本实现高水平的负载均衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Task scheduling optimisation algorithm based on load balance under the cloud computing environment
In order to achieve an optimal task scheduling scheme with the constraint of load balance in cloud computing platform. We utilise the CloudSim simulator to construct the cloud computing environment, and CloudSim contains three components: 1) CloudSim core simulation engine; 2) CloudSim basic structure; 3) user codes. Afterwards, we propose a novel load balancing oriented task scheduling optimisation algorithm based on genetic algorithm, and task assignment results are obtained through analysing gene values of chromosomes. In order to ensure convergence rate in genetic algorithm, we design the fitness function by integrating computation time and computation cost together. Furthermore, we design adaptive crossover and mutation operations to promote the search efficiency. Finally, we conduct an experiment to demonstrate the performance of the proposed algorithm. The experimental results show that the proposed algorithm can achieve the goal of high level of load balance with lower calculation time and cost.
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