An analysis of performance interference effects on energy-efficiency of virtualized cloud environments

Co-allocated workloads in a virtualized computing environment often have to compete for resources, thereby suffering from performance interference. While this phenomenon has a direct impact on the Quality of Service provided to customers, it also changes the patterns of resource utilization and reduces the amount of work per Watt consumed. Unfortunately, there has been only limited research into how performance interference affects energy-efficiency of servers in such environments. In reality, there is a highly dynamic and complicated correlation among resource utilization, performance interference and energy-efficiency. This paper presents a comprehensive analysis that quantifies the negative impact of performance interference on the energy-efficiency of virtualized servers. Our analysis methodology takes into account the heterogeneous workload characteristics identified from a real Cloud environment. In particular, we investigate the impact due to different workload type combinations and develop a method for approximating the levels of performance interference and energy-efficiency degradation. The proposed method is based on profiles of pair combinations of existing workload types and the patterns derived from the analysis. Our experimental results reveal a non-linear relationship between the increase in interference and the reduction in energy-efficiency as well as an average precision within +/-5% of error margin for the estimation of both parameters. These findings provide vital information for research into dynamic trade-offs between resource utilization, performance, and energy-efficiency of a data center.