Date Added: Feb 2012
User-perceived performance continues to be the most important QoS indicator in cloud-based data centers today. Effective allocation of Virtual Machines (VMs) to handle both CPU intensive and I/O intensive workloads is a crucial performance management capability in virtualized clouds. Although a fair amount of researches have dedicated to measuring and scheduling jobs among VMs, there still lacks of in-depth understanding of performance factors that impact the efficiency and effectiveness of resource multiplexing and scheduling among VMs. In this paper, the authors present the experimental research on performance interference in parallel processing of CPU-intensive and network-intensive workloads on Xen Virtual Machine Monitor (VMM). Based on their study, they conclude with five key findings which are critical for effective performance management and tuning in virtualized clouds.