Gaussian- based bidding strategies for service composition simulations

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Abstract

Service composition plays a crucial role in service–oriented computing allowing to deliver complex distributed applications obtained by aggregating autonomous and independent component services characterized by a given functionality and a Quality of Service. Automated negotiation is a viable approach to select component services according to their QoS values so to meet the end–to–end quality requirements of users requesting the application. This paper discusses the use of Gaussian probability functions to model negotiation strategies of service providers, and how the properties of these functions can be used to model multiple negotiations necessary for service composition as a single multi–issue negotiation. A numerical analysis shows comparable negotiation trends for the different representations of the service composition problem.

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Rossi, S., Nocera, D. D., & Di Napoli, C. (2016). Gaussian- based bidding strategies for service composition simulations. In Studies in Computational Intelligence (Vol. 638, pp. 193–208). Springer Verlag. https://doi.org/10.1007/978-3-319-30307-9_12

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