计算机技术与发展2016，Vol.26Issue(8)：24-29,6.DOI:10.3969/j.issn.1673-629X.2016.08.005
融合粒子群与蚁群的云计算任务调度算法
A Task Scheduling Algorithm of Cloud Computing Merging Particle Swarm Optimization and Ant Colony Optimization
摘要
Abstract
In cloud computing environment,there are a large number of users and tasks to be submitted by users. In order to make these tasks to be completed efficiently,how to schedule the tasks becomes the key of cloud computing. According to characteristics of cloud computing environment,improving Particle Swarm Optimization ( PSO) and Ant Colony Optimization ( ACO) ,a task scheduling algo-rithm combining PSO with ACO. It uses PSO to carry out the previous iteration,and selects a certain number of fine particles to generate the initial pheromone of ACO which carries out the post iteration by it,and then the final task scheduling result is obtained. The simulation shows that the algorithm is better than PSO and ACO,and decreases the total task completion time. It is an effective task scheduling algo-rithm.关键词
云计算/任务调度/粒子群优化/蚁群优化Key words
cloud computing/task scheduling/PSO/ACO分类
信息技术与安全科学引用本文复制引用
查安民,谭文安..融合粒子群与蚁群的云计算任务调度算法[J].计算机技术与发展,2016,26(8):24-29,6.基金项目
国家自然科学基金资助项目(6127036) （6127036）
上海第二工业大学重点学科(XXKZD1301) （XXKZD1301）
