Abstract
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.
Highlights
Service composition is a main problem in service based environment
In this paper we are going to find an approach in order to select the optimal composition among different feasible compositions, according to quality criteria of services by creation a Fuzzy-guided Genetic Algorithm System (FGS)
We set confidence factor of each quality criterion equal to 1 and draw charts related to changes of system variables
Summary
Service composition is a main problem in service based environment. Service composition means how the simple services aggregate to construct a new compound service with more value. Many researchers have worked on this problem. Heretofore, the diverse techniques have been presented based on different aspects for performing service composition [2],[3],[4],[5]. It is so important to find a composition whose cost is lower than all other feasible compositions can be made up. In this paper we are going to find an approach in order to select the optimal composition among different feasible compositions, according to quality criteria of services by creation a Fuzzy-guided Genetic Algorithm System (FGS)
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