Usages of Composition Search Tree in Web Service Composition
This work addresses the challenge for web service consumers who need to discover and compose services without knowing exact service names, though it appears incremental as an extension of previous research.
The paper tackles the problem of efficiently finding web service compositions that satisfy user requirements based on inputs and outputs, extending previous work by proposing the use of a Composition Search Tree to identify specific compositions of interest such as leanest and shortest depth compositions.
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.