面向多通道QoS需求的虚拟机分簇挖掘仿真

发布时间：2019-07-08 19:48

【摘要】：实行虚拟机最优分配方案的准确挖掘能够提高云计算的服务质量(Qo S)。利用传统算法进行虚拟机最优分配方案挖掘的过程中,由于受到大量冗余数据的影响,造成挖掘效率降低。为此,提出一种基于蚁群算法的面向多通道Qo S需求的虚拟机分簇挖掘方法。根据虚拟机特征的相似度对虚拟机进行分簇,利用蚁群算法进行虚拟机最优分配方案的挖掘,在此过程中,充分考虑了多用户对云计算中虚拟机资源服务质量(Qo S)的要求,避免出现同类型虚拟机被分配到同一物理机上的情况,同时,对蚁群算法中信息素的更新进行了优化。实验结果表明,利用改进算法进行虚拟机最优分配方案挖掘,能够有效提高挖掘效率,并降低系统负载均衡度。
文内图片：中的实验结果能够得知，，改进算法中的物

图片说明：中的实验结果能够得知，改进算法中的物
[Abstract]:The accurate mining of virtual machine optimal allocation scheme can improve the quality of service (Qo S).) of cloud computing. In the process of mining the optimal allocation scheme of virtual machine by using the traditional algorithm, the mining efficiency is reduced due to the influence of a large number of redundant data. In this paper, a virtual machine clustering mining method based on ant colony algorithm for multi-channel Qo S requirements is proposed. According to the similarity of virtual machine characteristics, virtual machine is grouped, and ant colony algorithm is used to mine the optimal allocation scheme of virtual machine. In this process, the requirements of multi-user for virtual machine resource quality of service (Qo S) in cloud computing are fully considered, and the situation that the same type of virtual machine is assigned to the same physical machine is avoided. At the same time, the update of pheromone in ant colony algorithm is optimized. The experimental results show that the improved algorithm can effectively improve the mining efficiency and reduce the load balance of the system by using the improved algorithm to mine the optimal allocation scheme of virtual machine.
【作者单位】：三江学院计算机科学与工程学院;南京航空航天大学计算机科学与技术学院;
【分类号】：TP302;TP311.13

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