Best web service selection based on the decision making between qos criteria of service

  • Authors:
  • Young-Jun Seo;Hwa-Young Jeong;Young-Jae Song

  • Affiliations:
  • Dept. of Computer Engineering, Kyunghee University, Gyeonggi-do, Republic of Korea;Faculty of General Education, Kyunghee University, Seoul, Republic of Korea;Dept. of Computer Engineering, Kyunghee University, Gyeonggi-do, Republic of Korea

  • Venue:
  • ICESS'05 Proceedings of the Second international conference on Embedded Software and Systems
  • Year:
  • 2005

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Abstract

Recently, extensive studies have been carried out on web service standards because of the necessity of developing large-scale applications in open environments. In particular, they enable services to be dynamically bound. However, current techniques fail to address the critical problem of selecting the right service instances. Service selection should be determined based on customer preferences and service level. We propose a best web service selection method which helps to find a service provider providing the optimal quality. Web service selection process was described with multi-criteria decision making approach(e.g. PROMETHEE) on the basis of evaluated values of qualities and the defined service level. The PROMETHEE method has advantages in comparison with the others(e.g. MAUT, AHP) as follows. First, the PROMETHEE method classifies alternatives which is difficult to be compared because of a trade-off relation of evaluation standards as non-comparable alternatives. Second, the PROMETHEE method is different from the AHP method in that there’s no need to perform a pair-wise comparison again when comparative alternatives are added or deleted. Therefore, this method is a suitable approach in the web service selection problem. Because the problem has a lot of quality parameters which are measured and evaluated at the same time and frequently induces a drop of another quality parameter by the improvement of one quality attribute. Consequently, our approach enables applications to be dynamically configured at runtime in a manner that continually adapts to the preferences of the customers. We verify our approach through case study.