Auction design for cross-edge task offloading in heterogeneous mobile edge clouds

Task offloading is a promising technology to exploit the available resources in edge cloud efficiently. Many incentive mechanisms for systems have been proposed. However, most of existing works study centralized under assumption that all mobile infrastructures are operated by central cloud. In this paper, we aim design auction-based truthful heavily loaded task system heterogeneous MECs. We first homogeneous MEC situation and present global auction executed as benchmark. For situation, model dual framework, which enables MECs perform cross-edge without participation servers. Specifically, two models: secondary model, offload tasks from large-scale region single auction, double suitable time sensitive tasks. Then auctions these models Through rigorous theoretical analysis, demonstrate proposed achieve desirable properties computational efficiency, individual rationality, budget balance, truthfulness, guaranteed approximation. The simulation results show can obtain 14.5% 4.2% more social welfare than comparison algorithm on average, respectively. addition, has great advantage terms computation efficiency.