Abstract
This paper presents an immune-inspired algorithm applied in the context of Web service composition to select the optimal composition solution. Our approach models Web service composition as a multi-layered process which creates a planning-graph structure along with a matrix of semantic links. We have enhanced the classical planning graph with the new concepts of service cluster and semantic similarity link. The semantic similarity links are defined between services on different graph layers and are stored in a matrix of semantic links. To calculate the degree of the semantic match between services, we have adapted the information retrieval measures of recall, precision and F_Measure. The immune-inspired algorithm uses the enhanced planning graph and the matrix of semantic links to select the optimal composition solution employing the QoS attributes and the semantic quality as the selection criteria.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Yan, Y., Zheng, X.: A Planning Graph Based Algorithm for Semantic Web Service Composition. In: Proc. of the 10th Conference on E-Commerce Technology and the Fifth Conference on Enterprise Computing, E-Commerce and E-Services, Washington DC, USA, pp. 339–342 (2008)
Gao, Y., et al.: Immune Algorithm for Selecting Optimum Services in Web Service Composition. Wuhan University Journal of Natural Sciences 11(1), 221–225 (2006)
Xu, J., Reiff-Marganiec, S.: Towards Heuristic Web Services Composition Using Immune Algorithm. In: Proc. of the International Conference on Web Services, Beijing, China, pp. 238–245 (2008)
Paolucci, M., et al.: Semantic Matching of Web Services Capabilities. In: Horrocks, I., Hendler, J. (eds.) ISWC 2002. LNCS, vol. 2342, pp. 333–347. Springer, Heidelberg (2002)
Skoutas, D., Simitsis, A., Sellis, T.: A Ranking Mechanism for Semantic Web Service Discovery. In: Proc. of the IEEE Congress on Services, Salt Lake City, UT, pp. 41–48 (2007)
Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach. Prentice Hall/Pearson Education, Upper Saddle River (2003)
Castro, L., von Zuben, F.: Learning and Optimization using the Clonal Selection Principle. Proc. of the IEEE Transactions on Evolutionary Computation, Special Issue on Artificial Immune Systems 6(3), 239–251 (2002)
McIlraith, S., Son, T.: Adapting Golog for Composition of Semantic Web Services. In: Proc. of the Eighth International Conference on Knowledge Representation and Reasoning (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pop, C.B., Chifu, V.R., Salomie, I., Dinsoreanu, M. (2010). Immune-Inspired Method for Selecting the Optimal Solution in Web Service Composition. In: Lacroix, Z. (eds) Resource Discovery. RED 2009. Lecture Notes in Computer Science, vol 6162. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14415-8_1
Download citation
DOI: https://doi.org/10.1007/978-3-642-14415-8_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14414-1
Online ISBN: 978-3-642-14415-8
eBook Packages: Computer ScienceComputer Science (R0)