A Truthful Auction Mechanism for Resource Allocation in Mobile Edge Computing

Offloading tasks from computing intensive mobile devices (MDs) to neighboring edge servers in the form of incentive mechanism can effectively reduce latency and increase utility in mobile edge computing (MEC). In this paper, we design an auction mechanism for a MEC system, and the system consists of multiple MDs and one service provider (SP). As the auctioneer, SP receives the bidding information from MDs, making resource allocation strategies by optimizing social welfare. An exact algorithm to solve social welfare maximization problem and a perturbation-based randomized allocation algorithm to achieve (1 - alpha) optimal social welfare approximation rate are proposed. Furthermore, we prove that the truthful random auction mechanism can achieves the auction properties, including individual rationality, incentive compatibility, weakly budget balance and computational efficiency in theory. Finally, simulation results show the effectiveness of the auction mechanism.