Grey relational analysis based cross-layer caching for content centric networking

In-networking caching is one of the most significant features in content centric network (CCN) to improve the content delivery efficiency. Some recent researches work on multi-metrics caching strategies to further improve the caching performance and caching space utilization. Nevertheless, it is still left open to deploy the correlation among multiple metrics. In this paper, a grey relational analysis (GRA) based cross-layer caching strategy is proposed. Firstly, user preference, betweenness centrality and caching replacement rate classified in application layer, network layer and physical layer, respectively are selected as the key metrics to caching strategy design. Then, an appropriate caching process based on GRA jointly considering the above three metrics of each node along the delivery path is developed. Simulation results demonstrate that the proposed strategy can achieve higher cache hit ratio and less average hops compared with well-known caching strategies.