Agile, efficient virtualization power management with low-latency server power states

• Authors: Canturk Isci;Suzanne McIntosh;Jeffrey Kephart;Rajarshi Das;James Hanson;Scott Piper;Robert Wolford;Thomas Brey;Robert Kantner;Allen Ng;James Norris;Abdoulaye Traore;Michael Frissora
• Venue: Proceedings of the 40th Annual International Symposium on Computer Architecture
• Year: 2013

One of the main driving forces of the growing adoption of virtualization is its dramatic simplification of the provisioning and dynamic management of IT resources. By decoupling running entities from the underlying physical resources, and by providing easy-to-use controls to allocate, deallocate and migrate virtual machines (VMs) across physical boundaries, virtualization opens up new opportunities for improving overall system resource use and power efficiency. While a range of techniques for dynamic, distributed resource management of virtualized systems have been proposed and have seen their widespread adoption in enterprise systems, similar techniques for dynamic power management have seen limited acceptance. The main barrier to dynamic, power-aware virtualization management stems not from the limitations of virtualization, but rather from the underlying physical systems; and in particular, the high latency and energy cost of power state change actions suited for virtualization power management. In this work, we first explore the feasibility of low-latency power states for enterprise server systems and demonstrate, with real prototypes, their quantitative energy-performance trade offs compared to traditional server power states. Then, we demonstrate an end-to-end power-aware virtualization management solution leveraging these states, and evaluate the dramatically-favorable power-performance characteristics achievable with such systems. We present, via both real system implementations and scale-out simulations, that virtualization power management with low-latency server power states can achieve comparable overheads as base distributed resource management in virtualized systems, and thus can benefit from the same level of adoption, while delivering close to energy-proportional power efficiency.