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Parallel and Distributed Processing Symposium, International (2011)
Anchorage, Alaska USA
May 16, 2011 to May 20, 2011
ISSN: 1530-2075
ISBN: 978-0-7695-4385-7
pp: 1034-1045
Good performance and efficiency, in terms of high quality of service and resource utilization for example, are important goals in a cloud environment. Through extensive measurements of an n-tier application benchmark (RUBBoS), we show that overall system performance is surprisingly sensitive to appropriate allocation of soft resources (e.g., server thread pool size). Inappropriate soft resource allocation can quickly degrade overall application performance significantly. Concretely, both under-allocation and over-allocation of thread pool can lead to bottlenecks in other resources because of non-trivial dependencies. We have observed some non-obvious phenomena due to these correlated bottlenecks. For instance, the number of threads in the Apache web server can limit the total useful throughput, causing the CPU utilization of the C-JDBC clustering middleware to decrease as the workload increases. We provide a practical iterative solution approach to this challenge through an algorithmic combination of operational queuing laws and measurement data. Our results show that soft resource allocation plays a central role in the performance scalability of complex systems such as n-tier applications in cloud environments.

L. Harada et al., "The Impact of Soft Resource Allocation on n-Tier Application Scalability," 25th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2011)(IPDPS), Anchorage, AK, 2011, pp. 1034-1045.
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