Commenced in January 2007
Paper Count: 29994
Elephant Herding Optimization for Service Selection in QoS-Aware Web Service Composition
Abstract:Web service composition combines available services to provide new functionality. Given the number of available services with similar functionalities and different non functional aspects (QoS), the problem of finding a QoS-optimal web service composition is considered as an optimization problem belonging to NP-hard class. Thus, an optimal solution cannot be found by exact algorithms within a reasonable time. In this paper, a meta-heuristic bio-inspired is presented to address the QoS aware web service composition; it is based on Elephant Herding Optimization (EHO) algorithm, which is inspired by the herding behavior of elephant group. EHO is characterized by a process of dividing and combining the population to sub populations (clan); this process allows the exchange of information between local searches to move toward a global optimum. However, with Applying others evolutionary algorithms the problem of early stagnancy in a local optimum cannot be avoided. Compared with PSO, the results of experimental evaluation show that our proposition significantly outperforms the existing algorithm with better performance of the fitness value and a fast convergence.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1132309Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
 L.Zeng, B. Benatallah, A.H.H. Ngu, M. Dumas, J. Kalagnanam, and H. Chang. Qos-aware middleware for web services composition. IEEE Trans. Softw. Eng, 2004.
 R. Marler and J. Arora. Survey of multi-objective optimization methods for engineering. International journal of Struct. Multidiscipl. Optim., 2004.
 A. Strunk, QoS-aware service composition: a survey, in: Proceedings of the 2010 Eighth IEEE European Conference on Web Services, ECOWS 10, IEEE Computer Society, Washington, DC, USA, 2010, pp. 6774.
 G.-G. Wang, S. Deb, and L. Coelho. Elephant herding optimization. In 3rd International Symposium on Computational and Business Intelligence, 2015.
 S. Yulu and C. Xi. A survey on qos-aware web service composition. In Third International Conference on Multimedia Information Networking and Security (MINES), 2011.
 G. Canfora, M. Penta, R. Espositio, and M. L. Villani. An approach for qos-aware service composition based on genetic algorithms. In conference on Genetic and eVolutionary computation GECCO 05, 2005.
 M. C. Jaeger and G. Muehl. Qos-based selection of services: The implementation of a genetic algorithm. In Communication in Distributed Systems (KiVS), 2007 ITG-GI Conference, 2007.
 W.C. Chang, C.S. Wu, and C. Chang. Optimizing dynamic web service component composition by using evolutionary algorithms. In IEEE International Conference on Web Intelligence, 2005.
 S.R.Dhore and M. Kharat. Qos based web services composition using ant colony optimization: mobile agent approach. International Journal of Advanced Research in Computer and Communication Engineering, 2012.
 Q. Wu and Q. Zhu. Transactional and qos-aware dynamic service composition based on ant colony optimization. Future Generation Comp. Syst, 2013.
 J. Gatha Jayjit and V. Gohel Piyush. Optimization with agent based approach. International Journal of Emerging Technologies and Innovative Research, 2015.
 W. Wang, Q. Sun, X. Zhao, and F. Yang. An improved particle swarm optimization algorithm for qos -aware web service selection in service oriented communication. International Journal of Computational Intelligence Systems, 2010.
 S. Kalepu, S. Krishnaswamy, and S. W. Loke. Verity: A qos metric for selecting web services and providers. In Proceedings of the Fourth International Conference on Web Information Systems Engineering Workshops (WISEW03), 2004.
 A. L. Lemos, F. Daniel, and B. Benatallah. Web service composition: A survey of techniques and tools, acm computing surveys. ACM Computing Surveys, 2015.
 E. Al-Masri and Q.H. Mahmoud, Qos-based discovery and ranking of web services. In Proceedings of 16th International Conference on Computer Communications and Networks, ICCCN, 2007.