Energy-Efficient Real-Time Heterogeneous Server Clusters

With increasing costs of energy consumption and cooling, power management in server clusters has become an increasingly important design issue. Current clusters for real-time applications are designed to handle peak loads, where all servers are fully utilized. In practice, peak load conditions rarely happen and clusters are most of the time underutilized. This creates the opportunity for using slower frequencies, and thus smaller energy consumption, with little or no impact on the Quality of Service (QoS), for example, performance and timeliness. In this work we present a cluster-wide QoS-aware technique that dynamically reconfigures the cluster to reduce energy consumption during periods of reduced load. Moreover, we also investigate the effects of local QoS-aware power management using Dynamic Voltage Scaling (DVS). Since most real-world clusters consist of machines of different kind (in terms of both performance and energy consumption) we focus on heterogeneous clusters. For validation, we describe and evaluate an implementation of the proposed scheme using the Apache Webserver in a small realistic cluster. Our experimental results show that using our scheme it is possible to save up to 45% of the total energy consumed by the servers, maintaining average response times within the specified deadlines and number of dropped requests within the required amount.