Towards energy-efficient reactive thermal management in instrumented datacenters

Abstract

Virtual Machine (VM) migration is one of the most common techniques used to alleviate thermal anomalies (i.e., hotspots) in cloud datacenter's servers of by reducing the load and, therefore, decreasing the server utilization. However, there are other techniques such as voltage scaling that also can be applied to reduce the temperature of the servers in datacenters. Because no single technique is the most efficient to meet temperature/performance optimization goals in all situations, we work towards an autonomic approach that performs energy-efficient thermal management while ensuring the Quality of Service (QoS) delivered to the users. In this paper, we explore ways to take actions to reduce energy consumption at the server side before performing costly migrations of VMs. Specifically, we focus on exploiting VM Monitor (VMM) configurations, such as pinning techniques in Xen platforms, which are complementary to other techniques at the physical server layer such as using low power modes. To support the arguments of our approach, we present the results obtained from an experimental evaluation on real hardware using High Performance Computing (HPC) workloads on different scenarios.