With the emergence and development of communication technology and new computing paradigm named mobile edge computing (MEC), fast response and ultralow latency are given higher requirements. Nevertheless, due to the low penetration and coverage of the MEC network, it is difficult to guarantee the large-scale connection needs of all user groups in industry 4.0. In addition, user mobility is closely related to the network connection between edge nodes (ENs) and mobile devices (MDs) in industry 4.0, the frequent mobility of MDs makes the computation offloading process not smooth and the channel unstable, which can reduce the network performance. Hence, this paper constructs an edge network environment for MEC-based industrial internet of things (IIoT), considering the combined benefits of energy consumption, time delay, and computing resource cost to tackle the aforementioned problem by maximizing the utility of the entire system. In order to solve this problem, this paper proposes a mobility-aware offloading and resource allocation scheme (MAORAS). This scheme first employs the Lagrange multiplier method to solve the problem of computing resource allocation; then, a noncooperative game between MDs is established and the existence of Nash equilibrium (NE) has been proven. Simulation results demonstrate that the practical performance of the MAORAS optimization scheme could improve the system utility significantly.
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