中文摘要：

为了实现云计算资源调度的多目标优化,提高资源利用率和保证云应用的服务质量,通过对云计算系统进行研究,设计并实现了一种基于RBF神经网络和粒子群算法的云计算资源动态调度系统.首先,提出云计算资源的动态调度系统的管理框架,并给出本框架形式;其次,设计并实现了一种综合运用RBF神经网络和改进粒子群算法,并通过预测资源的需求量、考虑应用性能、物理结点个数以及当前的负载情况的多目标资源调度方法.在Cloud Sim平台进行了仿真,实验结果表明提出的框架及算法能有效减少虚拟机迁移次数和物理结点的使用数量,提高资源的利用率的同时,也保证了云应用的服务质量,并具有较高的实用性和可行性.

英文摘要：

In order to implement the multi-objective optimization in Cloud Computing system and to improve the utilization ratio of the resource as well as guarantee application quality of service,the system of dynamic Resources scheduling system basing on PSO（ Particle Swarm Optimization） and RBF neural network has been designed and implemented after the study on the Cloud Computing.Firstly,a dynamic management framework has been proposed,providing the structure of the resources scheduling system.Secondly,a comprehensive service distribution algorithm has been designed and implemented in consideration of the amount of resources,each join points＇ performance and current load distribution.Finally,the result of the experiment indicates that he framework and the proposed algorithm can effectively reduce the number of virtual machine migration and the number of physical nodes use,the scheduling system can improve the efficiency of dispatching service and the utilization ratio in the Cloud Computing system.