欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
摘要：任务调度是云计算的关键问题之一，它的调度策略与算法直接影响到云计算系统的性能与成本。通过研究基于粒子群算法和遗传算法的任务调度策略，提出了一种基于进化策略的PSOCM算法。该算法通过在粒子群算法中引入遗传算法的交叉变异策略来提高粒子群算法的全局收敛效果，并且证明了PSOCM算法是一种全局收敛算法。Matlab仿真实验表明，该算法能够达到全局收敛，且收敛速度和稳定性优于传统的调度算法。
英文摘要：
Task scheduling is one of the key issues on the cloud computing, whose scheduling strategy and algorithm plays a direct effect on the performance and the cost of the cloud computing systems. By analyzing the particle swarm algorithm and the genetic algorithm, this paper proposes an evolutionary- strategy based PSO-CM algorithm to manage cloud tasks schedule. The proposed algorithm can improve the global convergence of PSO by introducing the crossover and mutation strategy of the genetic algorithm. The experiments on Matlab show that the proposed algorithm can achieve global convergence and is superior to the traditional scheduling algorithms in convergence speed and stability.
同期刊论文项目
同项目期刊论文
期刊信息
位置：