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2014 IEEE 7th International Conference on Cloud Computing (CLOUD) (2014)
Anchorage, AK, USA
June 27, 2014 to July 2, 2014
ISSN: 2159-6190
ISBN: 978-1-4799-5062-1
pp: 24-31
ABSTRACT
The performance unpredictability associated with migrating applications into cloud computing infrastructures has impeded this migration. For example, CPU contention between co-located applications has been shown to exhibit counter-intuitive behavior. In this paper, we investigate IO performance interference through the experimental study of consolidated n-tier applications leveraging the same disk. Surprisingly, we found that specifying a specific disk allocation, e.g., limiting the number of Input/Output Operations Per Second (IOPs) per VM, results in significantly lower performance than fully sharing disk across VMs. Moreover, we observe severe performance interference among VMs can not be totally eliminated even with a sharing strategy (e.g., response times for constant workloads still increase over 1,100%). By using a micro-benchmark (Filebench) and an n-tier application benchmark systems (RUBBoS), we demonstrate the existence of disk contention in consolidated environments, and how performance loss occurs when co-located database systems in order to maintain database consistency flush their logs from memory to disk. Potential solutions to these isolation issues are (1) to increase the log buffer size to amortize the disk IO cost (2) to decrease the number of write threads to alleviate disk contention. We validate these methods experimentally and find a 64% and 57% reduction in response time (or more generally, a reduction in performance interference) for constant and increasing workloads respectively.
INDEX TERMS
Servers, Interference, Time factors, Databases, Throughput, Virtual machine monitors, Software
CITATION

C. A. Lai, Q. Wang, J. Kimball, J. Li, J. Park and C. Pu, "IO Performance Interference among Consolidated n-Tier Applications: Sharing Is Better Than Isolation for Disks," 2014 IEEE 7th International Conference on Cloud Computing (CLOUD), Anchorage, AK, USA, 2014, pp. 24-31.
doi:10.1109/CLOUD.2014.14
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