Performance Measurement Through Caching in Named Data Networking Based Internet of Things

Abstract

Named Data Networking (NDN) is considered the future of Internet architecture, providing a realistic solution for data delivery using a caching module in an Internet of Things (IoT) based environment. However, a major challenge of the caching module is data redundancy, which decreases the overall caching performance by caching similar data at numerous locations in an NDN-based IoT scenario. Moreover, the latency and stretch are maximized due to high redundant caching operations. Several attempts have been made by the research community to provide an enhanced solution to overcome such issues. However, the caching module still requires efficient enhancement. This study provides critical insights into earlier caching strategies. To solve the problems of these caching strategies, an enhanced caching strategy is proposed, named Priority-based Content Popularity-Aware (PCPA) Caching Strategy, which is evaluated by comparing its performance with some of the novel NDN-based IoT caching strategies. The proposed caching strategy outperforms the comparing strategies in terms of latency, hop count, cache hit ratio and energy consumption.