Auction Pricing-Based Task Offloading Strategy for Cooperative Edge Computing

Mobile edge computing (MEC) enables resource-constrained mobile devices (MDs) to offload their tasks onto nearby edge servers. However, there exists a profit allocation problem between users and edge nodes (ENs) due to the limi-tations of ENs computing capacity and spectrum resources. In this paper, we propose an auction pricing-based MEC offloading strategy to maximize the profit of ENs. Firstly, we design an overall auction process using the binary offloading model by considering MDs battery capacity, basic profit, and tasks tolerable delay. Secondly, the bidding willingness of MDs in each round of auction are given on the premise of effectively ensuring users rationality. Finally, an auction pricing-based task offloading strat-egy is proposed, in which the winner of a single-round auction can offload its computation task to the ES. Simulation results verify the performance of the proposed strategy. Compared with the VA algorithm, the profit obtained by ENs has increased by 23.8%.