Abstract
An architecture for online discovery quantitative model of distributed service management based on genetic programming (GP) was proposed. The GP system was capable of constructing the quantitative models online without prior knowledge of the managed elements. The model can be updated continuously in response to the changes made in provider configurations and the evolution of business demands. The GP system chose a particular subset from the numerous metrics as the explanatory variables of the model. In order to evaluate the system, a prototype is implemented to estimate the online response times for Oracle Universal Database under a TPC-W workload. Of more than 500 Oracle performance metrics, the system model choose three most influential metrics that weight 76% of the variability of response time, illustrating the effectiveness of quantitative model constructing system and model constructing algorithms.
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Chen, J., Li, Zz., Wang, Yl. (2005). Distributed Service Management Based on Genetic Programming. In: Szczepaniak, P.S., Kacprzyk, J., Niewiadomski, A. (eds) Advances in Web Intelligence. AWIC 2005. Lecture Notes in Computer Science(), vol 3528. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11495772_14
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DOI: https://doi.org/10.1007/11495772_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26219-0
Online ISBN: 978-3-540-31900-9
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