Multi-edge node cooperative caching method based on deep neural network in mobile edge computing

The invention belongs to the technical field of caching, and particularly relates to a multi-edge node cooperative caching method based on a deep neural network in mobile edge computing, which comprises the following steps: constructing a prediction system of a mobile terminal action track based on the deep neural network, and predicting the position of a user at the next moment through the prediction system; constructing a hotspot service prediction system, and predicting hotspot data through the system; according to the predicted hotspot data, iteratively updating the cache through the predicted relationship between the user position and the node and according to the difference of the caches among the edge nodes; compared with a traditional LRU and a traditional LFU, the content with the highest popularity can be sensed in advance, and the resource utilization rate of a cache system is increased. 本发明属于缓存技术领域，具体涉及一种移动边缘计算中基于深度神经网络的多边缘节点协作缓存方法，包括构建基于深度神经网络的移动终端行动轨迹的预测系统，通过该预测系统预测下一时刻用户的位置；构建热点服务预测系统，通过该系统预测热点