A Distributed Heterogeneous Task Offloading Methodology for Mobile Edge Computing

With the rapid development of the Internet of Things (IoT), Mobile Edge Computing (MEC) becomes increasingly effective in improving processing capacity and providing low-latency computing services. However, in the time-varying MEC-IoT environment, heterogeneous devices and applications cause serious challenges on efficient task offloading and resource allocation. A Distributed Dynamic Heterogeneous task offloading Methodology (D2HM) algorithm is proposed in this paper by exploiting game theory and Lyapunov optimization, which can achieves heterogeneous control and allocation of computation resources by dynamic quote price mechanism. Simulation results show that the proposed algorithm can meet the diverse computing needs of heterogeneous tasks and reduce the average delay of the system while ensuring network stability.