摘要
Power control for virtualized enviromnents has is keeping underlying infrastructure in reasonably low power gained much attention recently. One of the major challenges states and achieving service-level objectives (SLOs) of upper applications as well. Existing solutions, however, cannot effectively tackle this problem for virtualized environments. In this paper, we propose an automated power control solution for such scenarios in hope of making some progress. The major advantage of our solution is being able to precisely control the CPU frequency levels of a physical environment and the CPU power allocations among virtual machines with respect to the SLOs of multiple applications. Based on control theory and online model estimation, our solution can adapt to the variations of application power demands. Additionally, our solution can simultaneously manage the CPU power control for all virtual machines according to their dependencies at either the application-level or the infrastructure-level. The experimental evaluation demonstrates that our solution outperforms three state-of-the-art methods in terms of achieving the application SLOs with low infrastructure power consumption.
Power control for virtualized enviromnents has is keeping underlying infrastructure in reasonably low power gained much attention recently. One of the major challenges states and achieving service-level objectives (SLOs) of upper applications as well. Existing solutions, however, cannot effectively tackle this problem for virtualized environments. In this paper, we propose an automated power control solution for such scenarios in hope of making some progress. The major advantage of our solution is being able to precisely control the CPU frequency levels of a physical environment and the CPU power allocations among virtual machines with respect to the SLOs of multiple applications. Based on control theory and online model estimation, our solution can adapt to the variations of application power demands. Additionally, our solution can simultaneously manage the CPU power control for all virtual machines according to their dependencies at either the application-level or the infrastructure-level. The experimental evaluation demonstrates that our solution outperforms three state-of-the-art methods in terms of achieving the application SLOs with low infrastructure power consumption.
基金
supported by the National Key Technology Research and Development Program of the Ministry of Science and Technology of China under Grant No.2012BAH46B03
the National HeGaoJi Key Project under Grant No.2013ZX01039-002-001-001
the Strategic Priority Research Program of the Chinese Academy of Sciences under Grant No.XDA06030200