云环境下基于粒子群优化的并行任务调度研究

R. Valarmathi, T. Sheela
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引用次数: 3

摘要

云计算是一种新兴的范式,它提供各种计算资源以满足不断发展的计算需求。由于云计算资源的复杂性、动态性、异构性、分布式等特点,使得任务调度面临诸多困难。任务调度的目标是最小化完工时间和最大化资源利用率。本文详细介绍了粒子群优化算法及其在云环境下任务调度中的几种变体。粒子群算法对任务调度问题有较好的解决效果。本文对PSO和任务调度的各个方面进行了深入的研究。
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A comprehensive survey on Task Scheduling for parallel workloads based on Particle Swarm optimisation under Cloud environment
Cloud Computing is a new emerging paradigm that provisions various computing resources to meet the developing computational needs. Scheduling the task poses many difficulties, because the cloud computing resources are complex, dynamic, heterogeneous, distributed in nature. Task Scheduling aims at minimising the makespan and maximising the resource utilisation. This paper gives an elaborate idea about Particle Swarm optimisation (PSO) algorithm and its several variants for task scheduling in cloud environment. PSO produces better results for task Scheduling Problems. This paper gives an insight to the researchers about various aspects of PSO and Task Scheduling.
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