The application claims a dynamic cooperative
perception content deployment optimization method, belonging to the field of mobile edge
network storage and
content distribution, specifically comprising: an
edge server collects historical traffic data of short video content, uses a GARCH model to extract volatility rate characteristics of the sequence, and inputs the same into a dynamic LSTM model with a fusion attention mechanism together with historical data to accurately predict
content popularity at the next moment. On this basis, an edge controller monitors
network link status in real time, dynamically calculates a cooperative
radius based on network load to determine a cooperation range; then, combined with predicted popularity, neighbor node cache status and
access time delay, the cooperative
gain of content is calculated, and a hierarchical cooperative deployment strategy is used to store content decisions in local nodes or overflow to neighbor nodes within the cooperative
radius. The application reduces
service time delay in
network congestion and traffic
mutation scenarios, and realizes virtual expansion of edge storage capacity and improvement of
cache hit rate through a neighbor cooperation mechanism.