Optimal Load Scheduling Based on Mobile Edge Computing Technology in 5G Dense Networking

Mobile Edge Computing (MEC) technology enables offloading of network tasks at the edge, combining edge IoT devices to provide proximity services for devices or terminals, solving the pressure and shortage of data storage, performance computing and decision analysis in the cloud platform. However, in the scenario of large-scale dense networking, the terminal deployment order is large and the tasks are large. Therefore, the system model based on mobile edge computing needs to be further optimized to meet the service requirements. In addition, the computing and storage resources of the edge computing nodes are limited, and there is a possibility of backlog of intensive task processing. Therefore, the mobile edge computing in the 5G intensive networking scenario still faces the task scheduling problem. Based on the above analysis, this paper proposes a task load balancing algorithm based on game theory. The algorithm can prove the upper limit of system cost by establishing a mathematical model for multi-terminal task processing and combining with the game mathematics theory to solve the optimal solution. he simulation results show that the algorithm proposed in this paper can reasonably utilize the edge resources and ensure the maximum benefit of the terminal equipment.