Abstract
Web has become the main platform for the interchange of information and the transaction of commerce. The performance of a Web system can be greatly improved by tuning its configuration parameters. However, there are dozens or even hundreds of tunable parameters in one Web system, and tuning can be the tough work even for the most experienced server administrators. Traditional Web tuning methods only focus on two or three specified parameters, and can not provide an effective solution to the tuning problem when the number of parameters is large. In this paper, we propose a feature selection algorithm based on Information Gain criterion to find the key parameters of a Web system. The algorithm can pick out the parameters that significantly affect Web system performance. Therefore, the tuning approach can be simplified dramatically. We have carried out extensive experiments with different Web systems. The results show that the algorithm is effective in searching the most important parameters under different conditions and reducing the time cost of next tuning steps.
This work is supported by National Natural Science Foundation of China (No. 60573090) and National Ministry of Education Project of China (GFA060448).
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Feng, S., Liu, Y., Wang, D., Shen, D. (2008). A Novel and Effective Method for Web System Tuning Based on Feature Selection. In: Zhang, Y., Yu, G., Bertino, E., Xu, G. (eds) Progress in WWW Research and Development. APWeb 2008. Lecture Notes in Computer Science, vol 4976. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78849-2_54
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DOI: https://doi.org/10.1007/978-3-540-78849-2_54
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