计算机与数字工程Issue(7)：1196-1201,1216,7.DOI:10.3969/j.issn1672-9722.2015.07.009
基于改进 NPGA 算法的多目标优化云任务调度算法
An Improved Multi-objective Optimization Algorithm Based on NPGA for Cloud Task Scheduling
摘要
Abstract
As cloud computing continues to evolve ,task scheduling under the traditional single‐objective optimization has been unable to meet the user's requirements for quality of service .This paper selects the running time and cost and load balance of establishing a multi‐objective optimization of cloud task scheduling model ,an improved multi‐objective niche Pare‐to genetic algorithm(NPGA) is proposed to speed up evolution and avoid premature convergence through a similar task se‐quence crossover(STOX) operating and shift mutation .In addition ,the size of comparison set and niche radius are selected a‐daptively to improve convergence speed .Simulation results show that improved NPGA algorithm is better to maintain diver‐sity and distribution of Pareto optimal solutions in the cloud scheduling .关键词
多目标优化/云任务调度/小生镜 Pareto 遗传算法/服务质量要求Key words
multi-objective optimization/cloud task scheduling/niche Pareto genetic algorithm/quality of service分类
信息技术与安全科学引用本文复制引用
杨燕..基于改进 NPGA 算法的多目标优化云任务调度算法[J].计算机与数字工程,2015,(7):1196-1201,1216,7.
