摘要
针对云计算环境下内置任务调度方法的低效问题,提出一种基于改进免疫进化算法的任务调度算法,利用人工免疫进化原理完成任务调度的全局优化。通过将粒子群优化算法作为算子嵌入免疫进化算法中,避免陷入局部最优,改善收敛效果,减少任务调度时间开销。以CloudSim作为仿真平台进行模拟,实验结果表明,改进的免疫进化算法能大幅提高云计算任务调度效率。
The task scheduling method built-in cloud computing environment is inefficient. A method based on improved immune evolutionary algorithm is proposed for task scheduling, which roots from artificial immune evolutionary theory to solve global optimize task scheduling on cloud computing. The improved immune evolutionary algorithm（Particle Immune Evolutionary Algorithm）PIEA introduces Particle Swarm Opt.imization（PSO） into immune evolutionary algorithm. PIEA improves the optimization ability compared with traditional immune evolutionary algorithm, and avoids local Optimization, the convergence of this method is better, and time consuming of task scheduling is reduced. The CloudSim simulation platform is chosen, and results indicate that PIEA can provide efficient task scheduling strategy.
出处
《计算机工程》
CAS
CSCD
2012年第9期208-210,共3页
Computer Engineering
基金
中央高校基本科研业务费专项基金资助项目(JUSRP10928)
江苏省普通高校研究生创新计划基金资助项目(CXLX11_0490)
无锡市科技支撑社会发展基金资助项目(CSE01014)
关键词
云计算
免疫进化
粒子群优化算法
任务调度
cloud computing
immune evolutionary
Particle Swarm Optimization（PSO） algorithm
task scheduling
