Energy Reduction in Consolidated Servers through Memory-Aware Virtual Machine Scheduling

Authors:
Jae-Wan Jang;Myeongjae Jeon;Hyo-Sil Kim;Heeseung Jo;Jin-Soo Kim;Seungryoul Maeng
Affiliations:
Korea Advanced Institute of Science and Technology (KAIST), Daejeon;Rice University, Houston;Korea Advanced Institute of Science and Technology (KAIST), Daejeon;Korea Advanced Institute of Science and Technology (KAIST), Daejeon;Sungkyunkwan University, Suwon;Korea Advanced Institute of Science and Technology (KAIST), Daejeon
Venue:
IEEE Transactions on Computers
Year:
2011

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Power-efficient distributed scheduling of virtual machines using workload-aware consolidation techniques

The Journal of Supercomputing

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Abstract

Increasing energy consumption in server consolidation environments leads to high maintenance costs for data centers. Main memory, no less than processor, is a major energy consumer in this environment. This paper proposes a technique for reducing memory energy consumption using virtual machine scheduling in multicore systems. We devise several heuristic scheduling algorithms by using a memory power simulator, which we designed and implemented. We also implement the biggest cover set first (BCSF) scheduling algorithm in the working server system. Through extensive simulation and implementation experiments, we observe the effectiveness of the memory-aware virtual machine scheduling in saving memory energy. In addition, we find out that power-aware memory management is essential to reduce the memory energy consumption.