Centrality-Based On-Path Caching Strategies in NDN-Based Internet of Things: A Survey

The substantial growth in data volume has led to considerable technological obstacles on the Internet. In order to address the high volume of Internet traffic, the research community has investigated the improvement of Internet architecture by implementing centrality-based caching, which could involve collaborative efforts. Different centrality-based caching strategies have been put forward that allow for different data distribution. These include betweenness centrality, degree centrality, and closeness centrality. Caching provides several advantages in terms of reducing latency, improving scalability, and enhancing data manageability. In addition, this study provides an overview of cache management algorithms based on centrality in the context of Information Centric Networking (ICN), Named Data Networking (NDN), and Internet of Things (IoT). It highlights the advantages and disadvantages of these algorithms and evaluates their performance in a network simulation environment, specifically in terms of cache hit ratio, data retrieval latency, and average hop count. Ultimately, we aim to pinpoint and deliberate on possible research directions for future studies concerning various aspects of centrality-based caching in communication systems.