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Issue No. 03 - July-Sept. (2013 vol. 6)
ISSN: 1939-1374
pp: 314-329
Calton Pu , Georgia Institute of Technology, Atlanta
Yuanda Cao , Beijing Institute of Technology, Beijing
Younggyun Koh , Georgia Institute of Technology, Atlanta
Sankaran Sivathanu , Georgia Institute of Technology, Atlanta
Ling Liu , Georgia Institute of Technology, Atlanta
Yiduo Mei , Xi'An Jiaotong University, Shanxi
Xing Pu , Beijing Institute of Technology, Beijing
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, we 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 our study, we conclude with five key findings which are critical for effective performance management and tuning in virtualized clouds. First, colocating network-intensive workloads in isolated VMs incurs high overheads of switches and events in Dom0 and VMM. Second, colocating CPU-intensive workloads in isolated VMs incurs high CPU contention due to fast I/O processing in I/O channel. Third, running CPU-intensive and network-intensive workloads in conjunction incurs the least resource contention, delivering higher aggregate performance. Fourth, performance of network-intensive workload is insensitive to CPU assignment among VMs, whereas adaptive CPU assignment among VMs is critical to CPU-intensive workload. The more CPUs pinned on Dom0 the worse performance is achieved by CPU-intensive workload. Last, due to fast I/O processing in I/O channel, limitation on grant table is a potential bottleneck in Xen. We argue that identifying the factors that impact the total demand of exchanged memory pages is important to the in-depth understanding of interference costs in Dom0 and VMM.
Interference, Throughput, Measurement, Virtual machine monitors, Hardware, Resource management, Servers, virtualization, Cloud computing, performance measurement
Calton Pu, Yuanda Cao, Younggyun Koh, Sankaran Sivathanu, Ling Liu, Yiduo Mei, Xing Pu, "Who Is Your Neighbor: Net I/O Performance Interference in Virtualized Clouds", IEEE Transactions on Services Computing, vol. 6, no. , pp. 314-329, July-Sept. 2013, doi:10.1109/TSC.2012.2
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