ISSN 1000-1239 CN 11-1777/TP

Journal of Computer Research and Development ›› 2020, Vol. 57 ›› Issue (1): 188-201.doi: 10.7544/issn1000-1239.2020.20190079

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Association Mining Based Consistent Service Configuration

Wang Tao1,2, Chen Wei2, Li Juan3, Liu Shaohua4, Su Lingang2, Zhang Wenbo1,2   

  1. 1(State Key Laboratory of Computer Science (Institute of Software, Chinese Academy of Sciences), Beijing 100190);2(Institute of Software, Chinese Academy of Sciences, Beijing 100190);3(Beijing University of Technology, Beijing 100124);4(Beijing University of Posts and Telecommunications, Beijing 100876)
  • Online:2020-01-01
  • Supported by: 
    This work was supported by the National Research and Development Program of China (2017YFB1400804), the National Natural Science Foundation of China (61872344), the Beijing Natural Science Foundation (4182070), and the Fund of the Youth Innovation Promotion Association of Chinese Academy of Sciences (2018144).

Abstract: Componentized service-oriented software systems always consist of loosely coupled hetero-geneous service components, each of which contains a large number of configuration items configured with high flexibility. Complex dependencies exist between service components, resulting in their interrelated configuration items, so the operations of deploying, updating and migrating components are prone to errors. For configuration items related with each other, changing one configuration item requires to modify other related configuration items. Otherwise, violating constraints perhaps happens, which should cause system failure. Therefore, analyzing associations between configuration items is one key to ensure the reliability of a system. This paper proposes a service configuration approach based on association mining. Our approach crawls configuration files from Internet, narrows the analysis scope to frequently changed configuration items, generates association coefficients for item pairs according to the similarity of items’ name, value and type, determines the set of candidate item pairs with rules, and then outputs a list of ordered configuration item pairs for query. We have deployed two typical open-source software systems to validate our approach for mining configuration associations between configuration items with case studies. Experimental results show that our approach can accurately detect most associations between configuration items.

Key words: association mining, service configuration, configuration association, error detection, service reliability

CLC Number: