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2013 IEEE International Conference on Services Computing (2013)
Santa Clara, CA, USA USA
June 28, 2013 to July 3, 2013
pp: 136-143
ABSTRACT
Performance unpredictability is one of the major concerns slowing down the migration of mission-critical applications into cloud computing infrastructures. An example of non-intuitive result is the measured n-tier application performance in a virtualized environment that showed increasing workload caused a competing, co-located constant workload to decrease its response time. In this paper, we investigate the sensitivity of measured performance in relation to two factors: (1) consolidated server specification of virtual machine resource availability, and (2) burstiness of n-tier application workload. Our first and surprising finding is that specifying a complete isolation, e.g., 50-50 even split of CPU between two co-located virtual machines (VMs) results in significantly lower performance compared to a fully-shared allocation, e.g., up to 100% CPU for both co-located VMs. This happens even at relatively modest resource utilization levels (e.g., 40% CPU in the VMs). Second, we found that an increasingly bursty workload also increases the performance loss among the consolidated servers, even at similarly modest utilization levels (e.g., 70% overall). A potential solution to the first problem (performance loss due to resource allocation) is cross-tier-priority scheduling (giving higher priority to shorter jobs), which can reduce the performance loss by a factor of two in our experiments. In contrast, bursty workloads are a more difficult problem: our measurements show they affect both the isolation and sharing strategies in virtual machine resource allocation.
INDEX TERMS
Time factors, Resource management, Servers, Interference, Software, Virtual machine monitors, Virtual machining
CITATION

Y. Kanemasa, Q. Wang, J. Li, M. Matsubara and C. Pu, "Revisiting Performance Interference among Consolidated n-Tier Applications: Sharing is Better Than Isolation," 2013 IEEE International Conference on Services Computing(SCC), Santa Clara, CA, USA USA, 2013, pp. 136-143.
doi:10.1109/SCC.2013.42
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