Preference-Based Web Service Composition: Case-Based Planning Approach

Abstract

Web service selection is an indispensable process for web service composition. However it became a difficult task as many web services are increased on the web and mostly they offer similar functionalities, which service will be the best. User preferences are the key to retain only the best services for the composition. In this paper, we have proposed a web service composition model based on user preferences. To improve the process of web service composition we propose a case-based planning approach with user preferences which uses successful experiences in past to solve similar problems. In this paper we integrate user preferences in the phase of selection, adaptation and planning. Our main contributions are a new method of case retrieval, an extended algorithm of adaptation and planning with user preferences. Results obtained offer more than a solution to the user and taking both functional and non- functional requirements. trip, preferences on particular transportation companies or hotels, and times/dates for the travel. Based on the assumption that the world is regular, so similar problems have similar solutions; As a consequence, solutions for similar problems are a useful starting point for new problem-solving. Case-based planning (CBP) is a problem-solving method that uses a library of cases, where a case associates a past problem and goal description with a plan that solves the problem by achieving the goal (5). In similar situations, CBP can take advantage of previous planning experiences by reusing stored plans. In this paper, we present a novel approach to compute the best service compositions based on user preferences and CBP. The proposed approach differs from the previous works in that user's preferences are taken into count as an additional input, so we model preferences and incorporate them into the user request. We use an algorithm to determine the relevant services that may be used to answer the composition request. We propose a new composition with user preferences if the request is not solved before and our system is learning from experiences. Our approach integrates the user preferences in the process of Case-Based Planning, the multi plan adaptation and the planning. We generate the plan for the user's new request by finding a composition plan from the library of cases. The newly generated plan together with the new request can now be stored as a case in the case base for future reuse. Many CBP retrieve and adapt a single plan (6) (7). We propose to retrieve multiple plans using an algorithm for retrieving based on two steps find and select according to the preferences. The sub-plans retrieved are merged and adapted to solve the problem.