Compound popular content caching strategy to enhance the cache management performance in named data networking

Named Data Networking (NDN) is a leading research paradigm for the future Internet architecture. The NDN offers in-network cache which is the most beneficial feature to reduce the difficulties of the location-based Internet paradigm. The objective of cache is to achieve a scalable, effective, and consistent distribution of information. However, the main issue which NDN facing is the selection of appropriate router during the content’s transmission that can disrupt the overall network performance. The reason is that how each router takes a decision to the cache which content needs to cache at what location that can enhance the complete caching performance. Therefore, several cache management strategies have been developed. Still, it is not clear which caching strategy is the most ideal for each situation. This study proposes a new cache management strategy named as Compound Popular Content Caching Strategy (CPCCS) to minimize cache redundancy with enhanced diversity ratio and improving the accessibility of cached content by providing short stretch paths. The CPCCS was developed by combining two mechanisms named as Compound Popular Content Selection (CPCS) and Compound Popular Content Caching (CPCC) to differentiate the contents regarding their Interest frequencies using dynamic threshold and to find the best possible caching positions respectively. CPCCS is compared with other NDN-based caching strategies, such as Max-Gain In-network Caching, WAVE popularity-based caching strategy, Hop-based Probabilistic Caching, Leaf Popular Down, Most Popular Cache, and Cache Capacity Aware Caching in a simulation environment. The results show that the CPCCS performs better in which the diversity and cache hit ratio are increased by 34% and 14% respectively. In addition, the redundancy and path stretch are decreased by 44% and 46% respectively. The outcomes showed that the CPCCS have achieved enhanced caching performance with respect to different cache size (1GB to 10GB) and simulation parameters than other caching strategies. Thus, CPCCS can be applicable in future for the NDN-based emerging technologies such as Internet of Things, fog and edge computing