Thesis Proposal: Dynamic optimization of power and performance for virtualized server clusters

This proposal presents an approach for power and performance management in a platform running multiple independent network applications, such as web-based applications. The approach assumes a virtualized server cluster environment and includes an associated optimization model and strategy developed to dynamically configure the applications over the processor’s cluster. The optimization aims to reduce the cluster power consumption, while meeting the performance requirements of the applications. An underlying mathematical formulation for power and performance optimization is given by a mixed integer programming model solved periodically at run-time in a control loop fashion. Dynamic configuration techniques, such as CPU dynamic frequency/voltage scaling, server on/off switching, virtual machine on-demand deployment and live migration, are investigated in order to implement the overall optimization approach.