Power and performance modeling of virtualized desktop systems

Abstract

Desktop virtualization is a new delivery method in which desktop operating systems execute in a data center and users access their applications using stateless “thin-client” devices. This paradigm promises significant benefits in terms of data security, flexibility, and reduction of the total cost of ownership. However, in order to further optimize this approach while maintaining good user experience, efficient resource management algorithms are required. This paper formulates an analytical model allowing for detailed investigation of how power consumption of virtualized server farm depends on properties of workload, adaptiveness of virtualization infrastructure, and average density of virtual machines per physical server. Assumptions needed to develop the model are confirmed using statistical analysis of desktop workload traces and the model itself is also validated using simulations. We apply the model to compare power consumption of static and dynamic virtual machine allocation strategies. The results of the study can be used to develop online virtual machine migration algorithms. Even though this paper focuses on virtualized systems running desktop workloads, the modeling approach is general and can be applied in other contexts.