An Efficient Algorithm for Strategy-Proof Service Composition

One of the most typical models of service market is a reverse auction, where service providers offer their services at a certain price and a user selects a combination of the services. In the first price auction, however, a service which is cheaper and has better quality is not necessarily selected. This causes unstable outcomes which are undesirable both for a user and service providers. A possible solution to this is the VCG (Vickrey-Clarke-Groves) mechanism, where the dominant strategy for a service provider is to report true cost of his service. In spite of this desirable property, implementing the VCG mechanism for service composition suffers from its computational cost. Calculation of payments to service providers based on the VCG mechanism requires iterative service selection, although each service selection can be NP- hard. Approximation algorithms cannot be applied because approximate solutions do not assure the desirable property of the VCG mechanism. Thus, we propose a dynamic programming (DP) based algorithm for service selection and VCG payment calculation. The proposed algorithm solves service selection in quasi-polynomial time and gives an exact solution. Moreover, we extend the algorithm to reuse matrix which is built during DP. This largely improves the performance of VCG payment calculation. Our experiment shows that the proposed algorithm can solve practical scale service composition.