Network Utility Maximization Based on an Incentive Mechanism for Truthful Reporting of Local Information

Abstract

Classic network utility maximization (NUM) problems are usually solved assuming all information is available, implying that information not locally available is always truthfully reported. This may not be practical in all scenarios, especially in distributed/semidistributed networks. In this paper, incentive for truthful reporting in network optimizations with local information is studied. A novel general model for extending NUM problems to incorporate local information is proposed, which allows each user to choose its own objective locally and/or privately. Two specific problems, i.e., a user-centric problem (UCP) and a network-centric problem (NCP), are studied. In the UCP, a network center aims to maximize the collective benefit of all users, and truthful reporting from the users regarding their local information is necessary for finding the solution. We show that the widely adopted dual pricing cannot guarantee truthful information reporting from a user unless the resource is oversupplied or the price is too high for this user to afford. In the NCP, the network center has its own objective and preferred solution, and incentive needs to be provided for the users to adopt the solution it prefers. Truthful reporting from the users is necessary for the center to determine the incentives and achieve its solution. For two-user and multiuser cases, we propose two mechanisms to motivate truthful reporting from the users, while guaranteeing nonnegative utility gains for both the users and the center. A case study on underlay device-to-device (D2D) communication illustrates the application of the UCP and the NCP. Simulations are conducted for the D2D application to validate the analytical results and demonstrate the proposed mechanisms.