云环境下基于改进NSGA II的虚拟机调度算法

在云环境中,如何将大量的虚拟机调度到物理节点上是一个基本且复杂的问题。文中首先对虚拟机的调度建立装箱问题模型,将该模型的求解转化一个多目标优化问题,目标分别为负载均衡、提高任务执行效率和降低能耗；接着对基于非支配排序的遗传算法（ Non-dominated Sorting Genetic Algorithm,NSGA II）进行改进,利用回溯法中的剪枝函数确定最优初始种群,引入正态分布密度函数限制优秀精英。仿真结果表明,基于改进NSGA II的虚拟机调度算法在任务执行时间、负载均衡和能量消耗三个方面优于其他一些常用算法。

Virtual Machines Scheduling Algorithm Based on Improved NSGA II in Cloud Environment

In cloud environment,how to schedule the large number of virtual machines to the physical nodes is a fundamental and difficult problem. Firstly,establish bin packing problem model based on virtual machines scheduling and solves the model through transforming it into a multi-objective optimization problem. The objectives respectively are load-balancing,to improve task-execution efficiency and to reduce energy consumption. Then,non-dominated sorting genetic algorithm is improved. The pruning function in the backtracking is used to confirm the optimal initial population. The normal distribution density function is introduced to restrict elite. The results of simulation show that the virtual machines scheduling algorithm based on improved NSGA II on the aspects of task execution time,load-balancing and energy consumption is better than other commonly used algorithms.