User-Centric Optimization for Constraint Web Service Composition using a Fuzzy-guided Genetic Algorithm System
This work addresses the challenge of user-centric optimization in service-oriented applications, but it appears incremental as it combines existing fuzzy logic and genetic algorithm techniques for a specific domain.
The paper tackled the problem of selecting optimal web service compositions that meet user preferences and non-functional constraints, such as cost or response time, by proposing a fuzzy-guided genetic algorithm system. The result showed that this system made user participation in web service composition easier and more efficient.
Service-Oriented Applications (SOA) are being regarded as the main pragmatic solution for distributed environments. In such systems, however each service responds the user request independently, it is essential to compose them for delivering a compound value-added service. Since, there may be a number of compositions to create the requested service, it is important to find one which its properties are close to user's desires and meet some non-functional constraints and optimize criteria such as overall cost or response time. In this paper, a user-centric approach is presented for evaluating the service compositions which attempts to obtain the user desires. This approach uses fuzzy logic in order to inference based on quality criteria ranked by user and Genetic Algorithms to optimize the QoS-aware composition problem. Results show that the Fuzzy-based Genetic algorithm system enables user to participate in the process of web service composition easier and more efficient.