A Combinatorial Auction Model for Composite Service Selection Based on Preferences and Constraints

We propose a novel market-based approach for dynamic composite service selection based on combinatorial auctions. The combinatorial auction model that we developed allows us to incorporate service providers' and requesters' preferences in the service selection process. From the providers' perspective, the combinatorial formulation allows them to express their preferences for offering combinations of services, or bundles. Moreover, the combinatorial model has the potential to lower the overall cost to the service requester as a result of providers offering discounts for service bundles. The proposed model also enables the service requester to express their preferences for the types of bundles by defining constraints over the configuration of the composite service provisioning, and data-cohesion of the bundles. We have mapped the problem to an Integer Linear Programming formulation and performed a number of experiments to evaluate the proposed model. In addition to demonstrating the relevance and applicability of combinatorial auction models for service selection, our experiments show that the cost of the composite service provisioning decreases with having more bidders in the auction, offering more crowded bundles is more profitable for service providers, and achieving high cohesion is more expensive than low cohesion for service requesters.