A Multilevel Index Model to Expedite Web Service Discovery and Composition in Large-Scale Service Repositories

Abstract— The number of Web services has grown drastically. Then how to manage them efficiently in a service repository is an important issue to address. Given a special field, there often exists an efficient data structure for a class of objects, e.g., the Google’ Bigtable is very suitable for Web pages’ storage and management.
Based on the theory of the equivalence relations and quotient sets, this work proposes a multilevel index model for large-scale service repositories, which can be used to reduce the execution time of service discovery and composition. Its novel use of keys as inspired by the key in relational database can effectively remove the redundancy of the commonly-used inverted index. Its four function-based operations are for the first time proposed to
manage and maintain services in a repository. The experiments validate that the proposed model is more efficient than the existing structures, i.e., sequential and inverted index ones. This development tendency has two following effects. One is that the number of services is rapidly enlarged. Another is that enormous services congregate into some service centers or service repositories. Therefore, the latter is more complicated than the former. It is especially difficult to realize the best composed services in a large-scale repository. < final year projects >