计算机工程与应用Issue(6)：84-88,5.DOI:10.3778/j.issn.1002-8331.1305-0042
基于粒子群遗传算法的云计算任务调度研究
Task scheduling algorithm based on Particle Swarm Optimization Genetic Algorithms in cloud computing environment
王波 1张晓磊1
作者信息
- 1. 重庆大学 计算机学院，重庆 400044
- 折叠
摘要
Abstract
How to schedule masses of tasks efficiently is an important issue to be resolved in cloud computing environment. An algorithm combining PSO and GA is brought up for user satisfaction and the needs of cloud providers. The algorithm, according to the characteristics of cloud environments to classify virtual machine resource, introduces the concept of the task-resources satisfaction distance and the comprehensive performance of resource. Then it optimizes the operation of initial particles to improve the quality of the particle in PSO. The algorithm fuses the operations of GA’s crossover and mutation and expands the search space of the particle to overcome the particles trapped in local optimal solution. The simulation result shows that the proposed algorithm is efficient to improve user satisfaction and reduce the completion time of the task.关键词
云计算/任务调度/遗传算法/粒子群算法Key words
cloud computing/task scheduling/Genetic Algorithm(GA)/Particle Swarm Optimization(PSO)分类
信息技术与安全科学引用本文复制引用
王波,张晓磊..基于粒子群遗传算法的云计算任务调度研究[J].计算机工程与应用,2015,(6):84-88,5.
