Abstract
Automatic web service composition has received a significant research attention in service-oriented computing over decades of research. With increasing number of web services, providing an end-to-end Quality of Service (QoS) guarantee in responding to user queries is becoming an important concern. Multiple QoS parameters (e.g., response time, latency, throughput, reliability, availability, success rate) are associated with a service, thereby, service composition with a large number of candidate services is a challenging multi-objective optimization problem. In this article, we study the multi-constrained multi-objective QoS-aware web service composition problem and propose three different approaches to solve the same, one optimal, based on Pareto front construction, and two others based on heuristically traversing the solution space. We compare the performance of the heuristics against the optimal and show the effectiveness of our proposals over other classical approaches for the same problem setting, with experiments on WSC-2009 and ICEBE-2005 datasets.
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