CCN Hotspot Cache Placement Strategy Based on Genetic Algorithm

Content-centric networks provide effective support for content services through a caching mechanism, so the caching of the placement strategy has become a hot research. In this paper, the problem of content placement in CCN is taken as the starting point, focusing on the allocation of caching resources for district partitioning according to the number of users given the content of predictable hotspots. When the hot topic breaks out, the first to the user from the content of the nearest as the goal, from the user’s point of view as its characteristics, nested using improved genetic algorithms to select hotspot cache placement points, and a CCN hotspot cache placement strategy based on genetic algorithm is proposed. In the simulation experiment, the cache placement strategy proposed in this paper is compared with other traditional strategies in network performance. The simulation results show that the strategy can effectively reduce the access hops and average access latency, reduce the server load and improve the user satisfaction.