基于粒子群算法的嵌入式云计算资源调度

Resource scheduling in embedded cloud computing based on particle swarm optimization algorithm

随着移动互联网的发展,基于嵌入式设备的云计算服务成为研究热点。在国内,嵌入式云计算目前正处于探索研究阶段,云资源管理调度是嵌入式云计算的核心技术之一,其效率直接影响嵌入式云计算系统的性能。为了提高云计算性能,本文提出一种基于粒子群优化算法的云计算任务调度模型。粒子群算法中粒子位置代表可行的资源调度方案,以云计算任务完成时间及资源负载均衡度作为目标函数,通过粒子群优化算法,找出最优资源调度方案。在matlab实验平台进行了仿真,通过大量数据模拟实验表明,该模型可以快速找到最优调度方案,提高资源利用率,具有较好的实用性和可行性。

With the development of mobile Internet,embedded cloud computing has become a research hotspot. In China, the embedded cloud computing is currently in the stage of exploration and research. In embedded cloud computing, in order to optimize the resource scheduling and improve the performance, the paper proposed a new task scheduling model based on particle swarm optimization （pso） algorithm.In this paper, the position of particles represent feasible resource scheduling scheme,the cloud computing task completion time and resource load balancing were taken as the objective function, the optimal resource scheduling scheme was obtained by the particle swarm optimization algorithm. The matlab simulation platform is selected for simulation,experimental results show that the proposed model can rapidly find the optimal scheduling scheme and enhances the utilization ratio , with better practicality and feasibility.