Title: Optimising the semantic web service composition process using bio-inspired methods

Authors: Viorica Rozina Chifu; Cristina Bianca Pop; Ioan Salomie; Dumitru Samuel Suia; Alexandru Niculici; Adela Negrean; Horatiu Jeflea

Addresses: Department of Computer Science, Technical University of Cluj-Napoca, Str. G. Baritiu nr. 26-28, 400027 Cluj-Napoca, Romania ' Department of Computer Science, Technical University of Cluj-Napoca, Str. G. Baritiu nr. 26-28, 400027 Cluj-Napoca, Romania ' Department of Computer Science, Technical University of Cluj-Napoca, Str. G. Baritiu nr. 26-28, 400027 Cluj-Napoca, Romania ' Department of Computer Science, Technical University of Cluj-Napoca, Str. G. Baritiu nr. 26-28, 400027 Cluj-Napoca, Romania ' Department of Computer Science, Technical University of Cluj-Napoca, Str. G. Baritiu nr. 26-28, 400027 Cluj-Napoca, Romania ' Department of Computer Science, Technical University of Cluj-Napoca, Str. G. Baritiu nr. 26-28, 400027 Cluj-Napoca, Romania ' Department of Computer Science, Technical University of Cluj-Napoca, Str. G. Baritiu nr. 26-28, 400027 Cluj-Napoca, Romania

Abstract: This paper presents two bio-inspired methods (one inspired by the cuckoo's breeding behaviour, and another one inspired by natural evolution and genetics) for selecting the optimal or near-optimal solution in web service composition. The proposed methods are applied on an enhanced planning graph structure which models the composition search space for a given user request. The cuckoo-inspired selection method applies a 1-OPT heuristic to expand the search space in a controlled way such that the stagnation in a local optimum solution is avoided. The genetic-based selection method uses two memory structures to avoid the stagnation in a local optimum solution on one hand, and to ensure that exploitation and exploration are properly performed. The quality of a composition solution is evaluated in terms of QoS attributes and semantic quality. To validate the proposed methods we have implemented an experimental prototype and carried out experiments on a set of scenarios with different complexities. Finally, we comparatively analyse the experimental results obtained by applying the two selection methods.

Keywords: optimal service composition; bio-inspired cpmputation; cuckoo search; genetic algorithms; weighted fitness function; optimisation; semantic web; web services; QoS attributes; quality of service; semantic quality.

DOI: 10.1504/IJBIC.2013.055451

International Journal of Bio-Inspired Computation, 2013 Vol.5 No.4, pp.226 - 238

Received: 01 Jun 2012
Accepted: 05 Oct 2012
Published online: 31 Mar 2014 *

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