QoS-Driven Web Service Composition Using Learning-Based Depth First Search

Abstract

The goal of the Web Service Composition (WSC) problem is to find an optimal composition of web services to satisfy a given request using their syntactic and/or semantic features. In this paper, in particular, we study the Quality of Services (QoS)-driven WSC problem to optimize service quality criteria, e.g., response time and/or throughput. We propose a novel solution based on Learning-based Depth First Search (LDFS). Given a set of web service descriptions including QoS information and a requirement web service, we reduce the QoS-driven WSC problem into a planning problem on a state-transition system. We then find the optimal solution for the problem using a dynamic programming based on LDFS which recently has shown a promising result.