Abstract
Service searching and ranking are the bases of service-oriented software development. However, the existing service searching and ranking methods are confined to the atomic services or processes encapsulated as stand-alone services. How to find and reuse arbitrary granularities of service process fragment (SPF) is a challenging problem with great application value. In this paper, we propose a new mechanism to support searching and ranking on massive SPF s. In this mechanism, SPF s are organized by a tree, where both the functional and non-functional information of SPF s are encoded and stored on each tree node. Then, starting from the tree root, an integrated searching and ranking process is recursively conducted on each tree layer, excluding a great deal of irrelevant SPF s each time, until leaf nodes are reached. To verify the feasibility and effectiveness, we construct a sample dataset which contains four million processes and one billion atomic services based on the Web Service Challenge Testset Generator (CTG) , and each atomic service has up to 10 QoS values. The experimental results show an effective and efficient approach for SPF- Query.
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