Combinatorial auction-based mechanism for task offloading in edge computing

In the era of the Internet of everything, the rapid increase in data volume and computation demand has prompted the evolution of application deployment mode from cloud computing to edge computing in order to reduce bandwidth consumption and response delay. However, there is a two-way selection problem between the application service provider (ASP) and the edge computing provider (ECP) in the process of task offloading. To solve this problem, this paper proposes a combinatorial auction- based mechanism for task offloading in edge computing. First, this paper establishes a system model, explains the key issues of model implementation, proposes a heuristic task selection algorithm for ECPs based on the analysis of their bidding process where choosing tasks to maximize resource utilization is proven to be an NP-complete problem, and then designs two auction algorithms, single-winner auction and multi-winner auction to fit trust-first and efficiency-first scenarios respectively. The experimental results show that compared with the single auction mechanism, the proposed scheme improves the utilization of ECP resources by 13%, and increases the utility of ASP by 37%.