Optimized Weight Vector for QoS Aware Web Service Selection Algorithm Using Particle Swarm Optimization

Authors: N. Arulanand, P. M. Ananth

Abstract:

Quality of Service (QoS) attributes as part of the service description is an important factor for service attribute. It is not easy to exactly quantify the weight of each QoS conditions since human judgments based on their preference causes vagueness. As web services selection requires optimization, evolutionary computing based on heuristics to select an optimal solution is adopted. In this work, the evolutionary computing technique Particle Swarm Optimization (PSO) is used for selecting a suitable web services based on the user’s weightage of each QoS values by optimizing the QoS weight vector and thereby finding the best weight vectors for best services that is being selected. Finally the results are compared and analyzed using static inertia weight and deterministic inertia weight of PSO.

Keywords: QoS, Optimization, Particle Swarm Optimization (PSO), weight vector, web services, web service selection.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1105393

References:

[1] Z. Stojanovic, A. Dahanayake and H. Sol, “Modeling and design of service oriented architecture”, in Proc. IEEE Int. Conf. Systems, Man and Cybernetics, Hague, Netherlands, Vol. 5, pp. 4147- 4152, Oct.2004.
[2] C.L. Huang and K. Yoon, “Multiple Criteria Decision-making”, Lecture Notes in Economics and Mathematical Systems, Springer-Verlag, New York, 1981.
[3] E. Al-Masri, and Q.H. Mahmoud, “Qos-based discovery and ranking of web services”, in Proc. 16th IEEE Int. Conf. Comp. Commun. Networks, pp. 529-534, 2007.
[4] J. L. Cohon and D.H. Marks, “A Review and Evaluation of Multiobjective Programming Techniques”, J. Water Res., Vol. 11, no. 2, pp. 208–220, April 1975.
[5] J. Kennedy and R.C. Eberhart, “Particle swarm optimization”, in Encyclopedia of Machine Learning, Springer US, 2010, pp. 760-766.
[6] X. Wang, T. Vitvar, M. Kerrigan and I. Toma, “A qos-aware selection model for semantic web services”, in Proc. 4th Int. Conf. Service- Oriented Comput. –ICSOC 2006. Springer Berlin Heidelberg, 2006. pp. 390-401.
[7] M. Paolucci, T. Kawamura, T.R. Payne, K. Sycara, “Semantic matching of web services capabilities”, Lecture Notes in Computer Science The Semantic Web—ISWC, Vol. 2342, 2002, pp 333-334.
[8] Y. Liu, A.H.H. Ngu and L. Zeng, “QoS Computation and Policing in Dynamic Web Service Selection”, in Proc. 13th Int. Conf. World Wide Web, New York, USA, pp. 66-73, 2004.
[9] X. Wang, T. Vitvar, M. Kerrigan and I. Toma, “A qos-aware selection model for semantic web services”, in Proc. 4th Int. Conf. Service- Oriented Comput. –ICSOC 2006. Springer Berlin Heidelberg, 2006. pp. 390-401.
[10] C. Rajeswary, “A survey on efficient evolutionary algorithms for web service selection”, Int. J. Manag. IT and Engg. Vol. 2, no. 9, pp. 177- 191, 2012.
[11] T. Zhang, “QoS-aware Web Service Selection based on Particle Swarm Optimization”, J. Netw., Vol. 9, no. 3, Mar. 2014, pp. 565-570.
[12] N. Arulanand., S.Subramanian, and K.Premalatha, “Optimized Bin Bloom Filter for Spam Filtering using Particle Swarm Optimization”, European J. Scientific Research, pp 199-213, 2012.
[13] Y. Liu, A.H.H. Ngu and L. Zeng, “QoS Computation and Policing in Dynamic Web Service Selection”, in Proc. 13th Int. Conf. World Wide Web, New York, USA, pp. 66-73, 2004.
[14] RC. Eberhart and S. Yuhui, “Particle swarm optimization: developments, applications and resources”, in Proc. 2001 EEE Int. Conf. Evol. Comput. Vol. 1, Seoul, South Korea, pp. 81-86, 2001.
[15] R.C. Eberhart and S. Yuhui, “Comparison between` genetic algorithms and particle swarm optimization”, Evolutionary Programming VII. Springer Berlin Heidelberg, Vol. 1447, 1998, pp 611-616.
[16] Y. Zhang, Z. Zheng, and M.R. Lyu, “Wsexpress: A qos-aware search engine for web services”, in Proc. IEEE 20th Int. Conf. Web Services, Miami, Floarida, pp. 91-98, 2010.
[17] E. Al-Masri, and Q.H. Mahmoud, “Discovering the best web service”, in Proc. 16thInt. Conf. World Wide Web, New York, USA, pp. 1257-1258, 2007.