Hybrid Optimization Algorithm for Large-Scale QoS-Aware Service Composition
This work addresses QoS-aware service composition for large-scale Web services, offering an incremental improvement over existing methods.
The paper tackles the problem of automatic Web service composition with optimal QoS and minimal services, presenting a hybrid optimization algorithm that outperforms state-of-the-art methods by achieving solutions with fewer services and optimal QoS.
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.