VCG Auction-Based Dynamic Pricing for Multigranularity Service Composition

When a single service on its own cannot fulfill a sophisticated application, a composition of services is required. Existing methods mostly use a fixed-price scheme for service pricing and determine service allocation for composition based on a first-price auction. However, in a dynamic service market, it is difficult for service providers to determine a fixed price that is profitable while attractive to customers. Meanwhile, this mechanism cannot ensure that the providers who require the least cost to provide services would win the auction, because the pricing strategy of service providers is unpredictable. To address such issues, in this paper, we propose Vickrey-Clarke-Groves auction-based dynamic pricing for a generalized service composition. We consider fine-grained services as candidates for composition as well as coarse-grained ones. In our approach, service providers bid for services of different granularities in the composite service and based on received bids, a user decides a composition that minimizes the social cost while meeting quality constraints. Experimental results at last verify the feasibility and effectiveness of the proposed approach. Note to Practitioners - Motivated by the popular auction-based dynamic pricing in the modern Internet business, this paper proposes a Vickrey-Clarke-Groves auction-based approach for multigranularity service composition in order to overcome the shortcomings of existing approaches, e.g., unpredictability in service pricing, and lack of economic efficiency. The proposed approach instantiates a composite service in an economically efficient way and it offers service providers with the incentives to honestly declare the true costs of their concrete services in the bids. In the experiments, compared with fine-grained service composition, the proposed approach reduces the social cost and user payment of service composition by 6.8% and 11.2% on average, respectively, and it also shows superiority over the first-price auction-based approach.