Modelling Task Offloading Mobile Edge Computing
Zhiyan Chen, Ligang He · 2022
With the rapid growth of mobile devices (such as smart phones and IoT devices) and the upcoming 5G era, it has been considered that edge computing will play a significant role, which together with the Cloud server forms the Mobile Edge Computing (MEC) platform. In MEC, it is desired that the tasks originated from the mobile devices can be offloaded to run on the edge devices or on the cloud. Namely, when a mobile device deems that it can benefit from not running its task locally (in terms of reducing the execution time), it will make the offloading decision to run the task on the edge. But when the total number of tasks offloaded from the mobile devices to the edge exceeds the capacity of the edge, some tasks may be further offloaded from the edge to the cloud server. In this paper, we aim to model the task offloading behavior in MEC. The game theory is utilized to establish the model. The mixed strategy for each mobile device (i.e., the probability that a mobile device offloads its task) at the Nash Equilibrium is derived. Further, the makespan of all the tasks running on the MEC platform is modelled. The extensive experiments have been conducted and the results show that the offload game modelled in this paper works effectively.