Autonomic Performance and Power Control for Co-located Web Applications on Virtualized Servers

Abstract—In a data center, various components of Web ap-plications co-located on virtualized servers exhibit complex time-varying interactions and interference. It has a significant impact on the user perceived performance and power consumption of the underlying system. We propose and develop APPLEware, an autonomic middleware for joint performance and power control of co-located Web applications. It features a distributed control structure that provides performance assurance and energy ef-ficiency for large complex systems. It applies machine learning based self-adaptive modeling to capture the complex and time-varying relationship between the application performance and allocation of resources to various application components, in the presence of highly dynamic and bursty workloads and inter-application performance interference. The distributed controllers perform coordinated resource allocation to meet the service level agreements of applications in an agile and energy-efficient man-ner. Experimental results based on a testbed implementation with benchmark applications demonstrate APPLEware’s effectiveness and energy efficiency