【摘要】 随着大数据服务领域引入云计算技术,需要调动的云服务资源增多且其拓扑结构变得复杂,因此传统基于服务质量(QoS)的加权评价方法无法动态地评价云计算服务资源的有效性和准确性。针对此问题,文中提出了一种基于博弈优化调度的筛选加权评价方法。此方法引入了用户的体验质量(QoE)评价指标,充分考虑了动态调度的业务和时延特性,通过多个指标的博弈,得到加权评价的参数的纳什均衡点。仿真实验结果表明,所提评估方法能够准确地评价云计算服务资源调度的有效性和准确性,并且适合大数据服务业务的拓展。更多还原

【Abstract】 With the introduction of cloud computing technology in the field of big data services,the traditional QoSbased weighted evaluation methods can not evaluate the validity and accuracy of cloud computing service resources dynamically due to the large number of cloud service resources which need to be mobilized and their complex topological structures.In order to solve this problem,this paper proposed a screening weighted evaluation method based on game optimization scheduling.This method introduces user’s QoE evaluation index,fully considers the service and delay characteristics of dynamic scheduling,and gets the Nash equilibrium point of weighted evaluation parameters through the game of multiple indexes.The simulation results show that the proposed evaluation method can accurately evaluate the validity and accuracy of cloud computing service resource scheduling and is suitable for the expansion of big data service business.更多还原