RAIM: A Reverse Auction-Based Incentive Mechanism for Mobile Data Offloading Through Opportunistic Mobile Networks

Abstract

Offloading cellular traffic through Opportunistic Mobile Networks (OMNs) has been an effective method to ease the traffic burden of cellular networks. However, providing data offloading services consumes a lot of resources. Since nodes in OMNs are rational and selfish, they will not be willing to provide data offloading services if they are not properly rewarded. Therefore, it is important to exploit incentive mechanisms to motivate nodes to provide data offloading services. This paper proposes a Reverse Auction-based Incentive Mechanism, named RAIM. In RAIM, reverse auction is used as the incentive mechanism, and the incentive-driven data offloading process is modeled as Non-Linear Integer Programming (NLIP) from the business point of view, aiming to minimize the cost of the Content Service Provider (CSP). Then, a heuristic method named Decay-based Helper Selection Method (DBHSM) is proposed to resolve the problem. Moreover, a payment rule based on the standard Vickrey-Clarke-Groves scheme is proposed to ensure the individual rationality and truthfulness properties of DBHSM. Finally, real mobility trace-driven simulation results show that DBHSM outperforms other baseline methods in terms of the CSP's cost and the offloading rate under different scenarios.