Research On Computation Offloading Strategy Of Mobile Edge Computing In Industrial Systems

With the increasing demand for digitization and intelligence of industrial production process,the demand for computiation resources of industrial system is increasing.As an emerging technology with high bandwidth and low latency,mobile edge computing can provide computing and storage services for industrial field equipment at the edge,and has become a research hotspot in the Industrial Internet field.This paper studies the computation offloading problem of moving edge computing in industrial system application.The main research contents are as follows:1)In order to slove problem that the network structure of multi-terminal singleedge server can easily lead to the performance degradation of edge server and the insufficient utilization of terminal computing resources,a partial computing offloading strategy based on particle swarm optimization(PSO)was proposed.This strategy is designed to achieve the performance and constraint conditions of the delay time demonstration when the task is completed,and the specific particle swarm algorithm is used to obtain the single-duration terminal calculation to complete the task,as well as the allocation method of indicator resources and computing resources.Simulation experiments show the convergence of the algorithm and can effectively reduce the processing delay of terminal tasks.2)Aiming at the network structure of multiple terminals and multiple edge servers,a computing offloading strategy based on intelligent search algorithm is proposed.In this strategy,a comprehensive performance index weighing time delay and energy consumption was designed.Particle swarm optimization was used to get the calculated unloading ratio,and the unloading vector was optimized based on genetic algorithm.The unloading part of each terminal was reasonably allocated to the edge server through centralized control.Simulation results show the effectiveness of the algorithm.