一种云计算环境下高效任务调度的混合算法

M. R. Thanka, P. Maheswari, E. Edwin
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引用次数: 9

摘要

云是一代人的福音,它提供的服务可以减少维护开销和计算复杂性。在云资源中调度用户的作业对于更好的性能起着重要的作用。任务调度是np困难问题,因为它可能有多个解决方案。本文提出了一种将人工蜂群算法与粒子群算法相结合的混合算法,称为ABPS算法。提出的ABPS算法通过提供最小的完工时间、成本、最大的资源利用率和平衡负载来优化云环境下的任务调度。在CloudSim仿真工具中对所提出的ABPS算法与ABC算法和PSO算法进行了仿真比较。本文提出的基于makespan的ABPS算法比ABC和PSO算法分别高出22.07%和28.12%,在成本方面比ABC和PSO算法分别高出32.41%和44.49%。基于资源利用率的ABPS算法比ABC和PSO算法分别高出49.37%和48.88%,基于失衡程度的ABPS算法比ABC和PSO算法分别高出16.21%和20.51%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A hybrid algorithm for efficient task scheduling in cloud computing environment
Cloud is a boon to the generation which provides services that can reduce the overhead in maintenance and computational complexities. Scheduling the user's job in the cloud resources plays an important role for the better performance. Task scheduling is an NP-hard problem, since it may have more than one solution to fit in. In this paper a hybrid algorithm is proposed by the amalgamation of artificial bee colony Algorithm and particle swarm optimisation named as ABPS algorithm. The proposed ABPS algorithm optimises the task scheduling on the cloud environment by providing minimised makespan, cost, and maximised resource utilisation and to balance the load. The proposed ABPS algorithm compared with ABC and PSO algorithm have been simulated in the CloudSim simulation tool. The proposed ABPS algorithm based on makespan outperforms ABC and PSO algorithms by 22.07% and 28.12%, respectively, also when compared with cost outperforms ABC and PSO algorithms by 32.41% and 44.49% respectively. ABPS algorithm based on resource utilisation outperforms ABC and PSO algorithms by 49.37% and 48.88% respectively and based on degree of imbalance outperforms ABC and PSO algorithms by 16.21% and 20.51% respectively.
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