A Bilateral Game Approach for Task Outsourcing in Multi-Access Edge Computing

Multi-access edge computing (MEC) is a promising architecture to provide low-latency applications for future Internet of Things (IoT)-based network systems. Together with the increasing scholarly attention on task offloading, the problem of servers' resource allocation has been widely studied. The limited computational resources of edge servers (ESs) cannot meet the different demands of terminal entities (TEs). This makes it a challenge to efficiently schedule computational tasks on ESs. In this paper, we consider a MEC resource transaction market with multiple ESs and multiple TEs, which are interdependent and mutually influence each other. This paper aims to investigate the dynamic tasks allocation problem between TEs and ESs and to meet the optimal benefits for both parties in MEC system. However, this many-to-many interaction requires resolving several problems, including task allocation, TEs' selection on ESs and conflicting interests of both parties. A bilateral game framework is applied to tackle the tasks allocation problem by modeling the problem as two noncooperative games: the supplier and customer side games. The existence and uniqueness of the Nash equilibrium in the aforementioned games are proved. A distributed task outsourcing algorithm (DTOA) is designed to determine the equilibrium. Our simulation results have demonstrated the superior performance of DTOA in increasing the ESs' profit and TEs' payoffs, as well as flattening the peak and off-peak loads.