Optimizing system configurations quickly by guessing at the performance

  • Authors:

  • Takayuki Osogami;Sei Kato

  • Affiliations:

  • IBM Tokyo Research Laboratory;IBM Tokyo Research Laboratory

  • Venue:
  • Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
  • Year:
  • 2007

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Abstract

The performance of a Web system can be greatly improved by tuning its configuration parameters. However, finding the optimal configuration has been a time-consuming task due to the long measurement time needed to evaluate the performance of a given configuration. We propose an algorithm, which we refer to as Quick Optimization via Guessing (QOG), that quickly selects one of nearly best configurations with high probability. The key ideas in QOG are (i) the measurement of a configuration is terminated as soon as the configuration is found to be suboptimal, and (ii) the performance of a configuration is guessed at based on the measured similar configurations, so that the better configurations are more likely to be measured before the others. If the performance of a good configuration has been measured, a poor configuration will be quickly found to be suboptimal with short measurement time. We apply QOG to optimizing the configuration of a real Web system, and find that QOG can drastically reduce the total measurement time needed to select the best configuration. Our experiments also illuminate several interesting properties of QOG specifically when it is applied to optimizing Web systems.