Stackelberg Game Based Edge Data Caching Strategy in 6G Data Plane

As the data infrastructure of the 6G network, the data plane (DP) takes on the management and consumption functions of new data elements such as sensing and intelligence. Data reuse is crucial to the various data sources and large volumes of data, making the location of data storage in DP especially important. In the cloud-edge architecture of 6G DP, collaborative edge caching is proposed in the radio access network (RAN). The caching strategy for data has a significant impact on caching performance. The decision-making process for data caching policy in DP is modeled using the Stackelberg game. This approach encourages the core network and the RAN to accurately cache data at the network edge based on users' requests. The Existence of Stackelberg Equilibrium is proved. A genetic-based iterative caching policy search algorithm (GESSA) is proposed to solve the optimal joint base station caching policy to maximize the utilities of both the core network and base stations. Numerical simulations show that compared with the existing schemes without considering data collaboration and benefits for both participants, the proposed scheme can effectively improve edge caching system utilities and provide lower data provision delay and higher hit rate for UEs.