Named Data Networking is an evolving network model of the Information-centric networking (ICN) paradigm which provides Named-based data contents. In-network caching is the responsible for dissemination of these contents in a scalable and cost-efficient way. Due to the rapid expansion of Internet of Things (IoT) traffic, ICN is envisioned to be an appropriate architecture to maintain the IoT networks. In fact, ICN offers unique naming, multicast communications and, most beneficially, in-network caching that minimizes the response latency and server load. IoT environment involves a study of ICN caching policies in terms of content placement strategies. This paper addressed the caching strategies with the aim to recognize which caching strategy is the most suitable for IoT networks. Simulation results show the impact of different IoT ICN-based caching strategies, out of these; periodic caching is the most appropriate strategy for IoT environments in terms of stretch that results in decreasing the retrieval latency and improves the cache-hit ratio.

The aim of named data networking (NDN) is to develop an efficient data dissemination approach by implementing a cache module within the network. Caching is one of the most prominent modules of NDN that significantly enhances the Internet architecture. NDN-cache can reduce the expected flood of global data traffic by providing cache storage at intermediate nodes for transmitted contents, making data broadcasting in efficient way. It also reduces the content delivery time by caching popular content close to consumers. In this study, a new content caching mechanism named the compound popular content caching strategy (CPCCS) is proposed for efficient content dissemination and its performance is measured in terms of cache hit ratio, content diversity, and stretch. The CPCCS is extensively and comparatively studied with other NDN-based caching strategies, such as max-gain in-network caching (MAGIC), WAVE popularity-based caching strategy, hop-based probabilistic caching (HPC), LeafPopDown, most popular cache (MPC), cache capacity aware caching (CCAC), and ProbCache through simulations. The results shows that the CPCCS performs better in terms of the cache hit ratio, content diversity ratio, and stretch ratio than all other strategies.

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Data communication in the present Internet paradigm is dependent on fixed locations that disseminate similar data several times. As a result, the number of problems has been generated in which location dependency is the most crucial for communication. Therefore, Named Data Networking (NDN) is a new network architecture that revolutionized the handling gigantic amount of data generated from diverse locations. The NDN offers in-network cache which is the most beneficial feature to reduce the difficulties of location-based Internet paradigms. Moreover, it mitigates network congestion and provides a short stretch path in the data downloading procedure. The current study explores a new comparative analysis of popularity-based cache management strategies for NDN to find the optimal caching scheme to enhance the overall network performance. Therefore, the content popularity-based caching strategies are comparatively and extensively studied in an NDN-based simulation environment in terms of most significant metrics such as hit ratio, content diversity ratio, content redundancy, and stretch ratio. In this analysis, the Compound Popular Content Caching Strategy (CPCCS) has performed better in terms to enhance the overall NDN-based caching performance. Therefore, it is suggested that the CPCCS will perform better to achieve enhanced performance in emerging environments such as, Internet of Things (IoT), Fog computing, Edge computing, 5G, and Software Defined Network (SDN). INDEX TERMS Content centric networking, information-centric networking, named data networking, caching.