得益于虚拟化技术的成熟发展，当下私有云和公有云数据中心已经越来越多的出现在企业、学校和研究机构当中。相对于物理机，虚拟机拥有更好的迁移性、可扩展性和相对低廉的购入与维护成本，所以越来越多的中小创业者倾向于购买虚拟机部署服务。对于云服务提供者来说，如何在满足 SLA 情况下对云环境下或者运行于同一物理资源池上的虚拟机合理分配资源从而实现硬件资源池最大化利用变得越来越重要。本文分析了影响虚拟环境下虚拟机应用性能的关键参数，并证明了虚拟机应用性能与硬件资源之间存在着复杂的非线性关系，通过一种 SVD 特征拓展+非线性模型的方法对运行于同一物理资源池上的虚拟机应用性能进行建模研究，实验表明该模型有较好的效果，并且平均预测误差可以达到12%左右。%Thanks to the development of virtualization technology, the private and public cloud data center has more and more appeared in enterprises, schools and research institutions. Relative to the physical machine, the virtual machine has better mobility,scalability,and relatively cheap to buy and maintenance, so more and more small and medium-sized entrepreneurs tend to buy virtual machine deployment services. So for cloud service providers, how to allocate physical resources to the VMs in one cloud environment and maximize the utilization of hardware resources pool meeting SLA is becoming more and more important. In this paper, we analyzed the key parameters that affect the VMs’ application performance, we used a method of SVD + non-linear model in the application performance modeling and a good results were obtained in the experiment that makes the average prediction error can reach about 12%.
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