An Efficient Power-Aware Resource Scheduling Strategy in Virtualized Datacenters

Abstract

In the era of cloud computing, data centers are well-known to be bounded by the power wall issue. This issue lowers the profit of service providers and obstructs the expansions of data center's scale. As virtual machine's behavior was not explored sufficiently in classic data center's power-saving strategies, in this paper we address the power consumption issue in the setting of a virtualized data center. We propose an efficient power-aware resource scheduling strategy that reduces data center's power consumption effectively based on VM live migration which is a key technical feature of cloud computing. Our scheduling algorithm leverages the Xen platform and consolidates VM workloads periodically to reduce the number of running servers. To satisfy each VM's service level agreements, our strategy keeps adjusting VM placements between scheduling rounds. We developed a power-aware data center simulator to test our algorithm. The simulator runs in time domain and includes server's segmented linear power model. We validated our simulator using measured server power trace. Our simulation shows that compared with event-driven schedulers, our strategy improves data center power budget by 35% for random workloads resembling web-requests, and improve data center power budget by 22.7% for workloads exhibiting stable resource requirements like ScaLAPACK.