Performance Improvement of Distributed Systems by Autotuning of the Configuration Parameters |
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| Authors: | Fan Zhang 张帆 Junwei Cao 曹军威 Lianchen Liu 刘连臣 Cheng Wu 吴澄 |
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| Affiliation: | aNational CIMS Engineering and Research Center, Tsinghua University, Beijing 100084, China;bResearch Institute of Information Technology, Tsinghua University, Beijing 100084, China;cTsinghua National Laboratory for Information Science and Technology, Beijing 100084, China |
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| Abstract: | The performance of distributed computing systems is partially dependent on configuration parameters recorded in configuration files. Evolutionary strategies, with their ability to have a global view of the structural information, have been shown to effectively improve performance. However, most of these methods consume too much measurement time. This paper introduces an ordinal optimization based strategy combined with a back propagation neural network for autotuning of the configuration parameters. The strategy was first proposed in the automation community for complex manufacturing system optimization and is customized here for improving distributed system performance. The method is compared with the covariance matrix algorithm. Tests using a real distributed system with three-tier servers show that the strategy reduces the testing time by 40% on average at a reasonable performance cost. |
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| Keywords: | distributed systems performance evaluation autotune configuration parameters ordinal optimization covariance matrix algorithm |
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