Hybrid Optimization Algorithm for Large-Scale QoS-Aware Service Composition

TL;DR

This paper introduces a hybrid optimization approach for large-scale, QoS-aware web service composition that efficiently generates minimal service compositions with optimal end-to-end QoS, outperforming existing methods.

Contribution

The paper proposes a novel hybrid local-global search method that effectively reduces search space and finds optimal, minimal-service web service compositions considering QoS.

Findings

Hybrid approach outperforms state-of-the-art methods

Achieves compositions with fewer services and optimal QoS

Validated on Web Service Challenge datasets and synthetic data

Abstract

In this paper we present a hybrid approach for automatic composition of Web services that generates semantic input-output based compositions with optimal end-to-end QoS, minimizing the number of services of the resulting composition. The proposed approach has four main steps: 1) generation of the composition graph for a request; 2) computation of the optimal composition that minimizes a single objective QoS function; 3) multi-step optimizations to reduce the search space by identifying equivalent and dominated services; and 4) hybrid local-global search to extract the optimal QoS with the minimum number of services. An extensive validation with the datasets of the Web Service Challenge 2009-2010 and randomly generated datasets shows that: 1) the combination of local and global optimization is a general and powerful technique to extract optimal compositions in diverse scenarios; and 2) the hybrid strategy performs better than the state-of-the-art, obtaining solutions with less services and optimal QoS.