Migration energy-aware workload consolidation in enterprise clouds

New schemes to pack applications that targets a joint optimization of energy and performance overhead of VM migrations are devised that can improve energy savings up to 23% compared to state of the art power-aware workload consolidation strategy.

Abstract

Consolidation through live VM migrations is a promising approach to improve server utilization. However, prior consolidation works have focused mostly on the performance impact of migration and neglected the associated energy overhead. Our research finds that energy impact of migration can offset over 12 % of the energy saved through energy-conscious workload packing. To address this limitation of the current state of research, in this paper we devise new schemes to pack applications that targets a joint optimization of energy and performance overhead of VM migrations. Additionally, we develop a statistical workload modeling technique for simulating consolidation problem in enterprise cloud contexts. Our experiments with statistically generated synthetic trace and Google's production trace demonstrate that our schemes can improve energy savings up to 23% compared to state of the art power-aware workload consolidation strategy.