Evolutionary Game Caching Resource Allocation Strategy for 6G Networks

Network slicing is a key technology in sixth-generation (6G) communication networks. However, the performance of virtualized nodes sharing cache resources in 6G network slicing is degraded by the inappropriate allocation of resources. This paper proposes a cache resource allocation strategy for 6G network slicing based on game dynamics (RASGD). A 6G slicing network model is developed that describes the relationship between virtualized node mapping and resource sharing, and an evolutionary public goods game cache resource allocation (PGGRA) method is proposed to improve data transmission performance. This strategy defines the cache resource gap and selects the input cost according to the cache resource gap and evolutionary game strategy. When the cache resources are sufficient, the input is carried out, and when the cache resources are insufficient or the demand is large, unnecessary input is reduced to avoid the waste of resources, so as to achieve the intelligent allocation of cache resource. Simulation results demonstrate that the RASGD strategy improves the successful arrival rate of slice packets by at least 4.79% and improves the network congestion by at least 22.9% compared with the resource allocation strategy based on number of nodes (RANN) and resource allocation strategy based on node degree (RAND).