The increasing availability of web services within an organization and on the Web demands for efficient search and composition mechanisms to find services satisfying user requirements. Often consumers may be unaware of exact service names that is fixed by service providers. Rather consumers being well aware of their requirements would like to search a service based on their commitments (inputs) and expectations (outputs). Based on this concept we have explored the feasibility of I O based web service search and composition in our previous work. The classical definition of service composition, i.e., one-to-one and onto mapping between input and output sets of composing services, is extended to give rise to three types of service match: Exact, Super and Partial match. Based on matches of all three types, different kinds of compositions are defined: Exact, Super and Collaborative Composition. Process of composition, being a match between inputs and outputs of services, is hastened by making use of information on service dependency that is made available in repository as an one time preprocessed information obtained from services populating the registry. Adopting three schemes for matching for a desired service outputs, the possibility of having different kinds of compositions is demonstrated in form of a Composition Search Tree. As an extension to our previous work, in this paper, we propose the utility of Composition Search Tree for finding compositions of interest like leanest and the shortest depth compositions.
The current techniques based on relational database are constrained by usage of multiple joins as well as malady of exact match of input and output parameters.In @cite_6 we propose an approach to overcome these difficulties. The criteria for matching is relaxed for partial matching allowing several services to collaborate and provide a desired service. In the current work we further extend the utility of Composition Search Tree for finding optimal service compositions.
@cite_6
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Relational Database for its huge success in data management has been used here as a scalable repository for storing webservices in UDDI framework. The operator ‘join’ has been used to derive service composition by matching inputs of a service to outputs of another. Adopting three modes of composability for a desired service, the possibility of having different kinds of compositions is demonstrated in form of a Composition Search Tree.