Virtual Machine packing algorithms for lower power consumption
Virtual Machine packing algorithms for lower power consumption
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DOI：
10.1109/sc.companion.2012.300
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发表时间：
2012-11
期刊：
影响因子：
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通讯作者：
Satoshi Takahashi;A. Takefusa;Maiko Shigeno;H. Nakada;T. Kudoh;Akiko Yoshise
中科院分区：
文献类型：
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作者：
Satoshi Takahashi;A. Takefusa;Maiko Shigeno;H. Nakada;T. Kudoh;Akiko Yoshise
基于虚拟机的灵活容量管理是降低数据中心总功耗的有效方案。然而，在节能和用户体验之间的权衡，在可行的计算时间内决定虚拟机打包计划，以及多虚拟机动态迁移过程的避免冲突等问题仍然存在。为了解决这些问题，我们提出了两种VM打包算法，基于匹配的（MBA）和贪婪型启发式（GREEDY）。MBA能够在多项式时间内确定最优计划，而GREEDY是一种比MBA更快的激进打包方法。我们分别在人工和真实仿真场景下研究了所提出算法的基本性能和可行性。基础性能实验表明，该算法将总功耗降低了18% ~ 50%，并且在可行的计算时间内给出了合适的VM封装方案。可行性实验表明，本文提出的算法在实际超级计算机上制定包装计划是可行的，并且GREEDY算法在功耗上具有优势，而MBA算法在用户体验上表现出更好的性能。
Virtual Machine(VM)-based flexible capacity management is an effective scheme to reduce total power consumption in the data centers. However, there remain the following issues, trade-off between power-saving and user experience, decision on VM packing plans within a feasible calculation time, and collision avoidance for multiple VM live migration processes. In order to resolve these issues, we propose two VM packing algorithms, a matching-based (MBA) and a greedy-type heuristic (GREEDY). MBA enables to decide an optimal plan in polynomial time, while GREEDY is an aggressive packing approach faster than MBA. We investigate the basic performance and the feasibility of proposed algorithms under both artificial and realistic simulation scenarios, respectively. The basic performance experiments show that the algorithms reduce total power consumption by between 18% and 50%, and MBA makes suitable VM packing plans within a feasible calculation time. The feasibility experiments show that the proposed algorithms are feasible to make packing plans for an actual supercomputer, and GREEDY has the advantage in power consumption, but MBA shows the better performance in user experience.