Multilayer satellite network collaborative mobile edge caching: A GCN-based multi-agent approach

With the explosive growth of high definition video streaming data, a substantial increase in network traffic has ensued. The emergency of mobile edge caching (MEC) can not only alleviate the burden on core network, but also significantly improve user experience. Integrating with the MEC and satellite networks, the network is empowered popular content ubiquitously and seamlessly. Addressing the research gap between multilayer satellite networks and MEC, we study the caching placement problem in this paper. Initially, we introduce a three-layer distributed network caching management architecture designed for efficient and flexible handling of large-scale networks. Considering the constraint on satellite capacity and content propagation delay, the cache placement problem is then formulated and transformed into a markov decision process (MDP), where the content coded caching mechanism is utilized to promote the efficiency of content delivery. Furthermore, a new generic metric, content delivery cost, is proposed to elaborate the performance of caching decision in large-scale networks. Then, we introduce a graph convolutional network (GCN)-based multi-agent advantage actor-critic (A2C) algorithm to optimize the caching decision. Finally, extensive simulations are conducted to evaluate the proposed algorithm in terms of content delivery cost and transferability.