一种用于云计算资源调度的双向蚁群优化算法

A Bidirectional Ant Colony Optimization Algorithm for Cloud Computing Resource Scheduling

摘要:

对云计算环境中的资源调度问题进行了研究,针对蚁群优化算法(ACO)在处理大规模组合优化问题时易陷入搜索速度慢和局部最优解的缺陷,提出了一种实现云计算负载均衡的双向蚁群优化算法(BACO)用于资源调度;该算法考虑到了每个虚拟机的负载和计算能力,同时在云环境中引入了蚂蚁的向前移动和向后移动;最后通过在CloudSim平台进行仿真实验,结果表明该算法的总任务完成时间较短,具有较好的寻优能力,并且能够实现负载均衡,是一种有效的资源调度算法。

Abstract:

The resource scheduling problem in the environment of the cloud computing is studied.Concerning ant colony optimization(ACO) algorithm in solving the large-scale combination optimization problem easy to fall into the search speed slowly and partially the most superior,a bidirectional ant colony optimization(BACO) algorithm implementation of cloud computing load balancing for resource scheduling is proposed.This algorithm considers the load and computing capacity of each virtual machine.At the same time forward movement of ants and backward movement of ants are introduced in the cloud environment.Finally,the experiment simulated on CloudSim platform shows that the algorithm enables the reduce of total task completion time and has good effect in optimization capability and load balancing.It is proved to be an effective resource scheduling algorithm.