Research on task offload for edge computing in high-speed railway vehicle ground communication network

As the key technology of Intelligent Railway 5g network, edge computing sinks the data caching capacity, traffic forwarding capacity and application service capacity to the edge of the network, effectively meeting the requirements of Intelligent Railway for low delay, large bandwidth and massive connection, so as to support the application of intelligent rail transit. However, due to the complexity and high dynamics of the high-speed railway operation environment, its train ground communication network has some problems, such as poor transmission stability, low throughput, limited wireless resources between trains and ground, and low utilization efficiency. In order to further optimize scheduling resources and improve system performance, this paper studies the task unloading problem of mobile edge computing (MEC) in the high-speed railway train ground communication network, A task unloading scheme is designed, and the effectiveness of the scheme is verified by simulation.