一种能耗-性能协调优化的虚拟机重放置策略

在云计算环境中虚拟机重放置方法方面，现有多数算法通常聚焦单一目标的优化，而聚焦一个单一目标通常会牺牲其他目标来达到最优效果，因此有必要考虑多目标权衡的虚拟机重放置方法。以降低能耗和保证虚拟机的服务质量为目标，提出一种能耗-性能协调的虚拟机重放置优化算法,即能耗-性能优化配合降序最佳适应算法（Energy-Performance awareness best fit descending virtual machine relocating，EPAR），把资源使用率转化为能耗，同时权衡了能耗和性能之间的关系。该算法在选择重放置虚拟机时使用自回归模型预测下一时间段的性能。通过原型验证，EPAR算法能够在确保虚拟机服务的情况下，有效降低宿主机的能耗，避免不必要的虚拟机的迁移。

The Virtual Machine Relocating Strategy with Collaborative Optimization between Energy and Performance

Most of existing virtual machine relocating algorithms usually focuses on the optimization of single goal in cloud computing environment, usually sacrificing other goals to achieve the optimal effect. Therefore this paper presents a virtual machine relocating strategy with multi-goal tradeoff. To decrease energy consumption and guarantee the service quality of virtual machines, the paper puts forward a virtual machine relocating algorithm of collaborating between energy and performance, called Energy-Performance awareness best fit descending virtual machine relocating (abbr. EPAR), in which the resource utilization is converted into energy consumption and there is a tradeoff between energy consumption and performance at the same time. The algorithm effectively avoids the unnecessary migration by using an autoregressive model to predict the performance of the next period of time. The prototype verifies that the algorithm is able to ensure the service capability of virtual machine, as well as to reduce energy consumption effectively and avoid unnecessary virtual machine migration.