Analytical characterization of data popularity based caching method in Named Data Networks

In response to the increasing demand for efficient and scalable content distribution, Information-Centric Networking (ICN) has emerged as a promising solution for future Internet architecture. One of the key components of ICN is in-network caching, which aims to reduce content delivery time by temporarily storing data in the network. In this context, the cache replacement policy plays a crucial role in determining which content should be retained or discarded when cache space is limited. This paper focuses on the analytical characterization of a data popularity-based caching method in Named Data Networks (NDN). We propose a detailed theoretical analysis of the impact of this caching policy on user experience metrics, specifically hit ratio, average content delivery time and caching cost. Using the presented theoretical analysis, first in terms of hit rate, overall data retrieval delay, and cache cost, we present a comparison between the FBC method and original NDN. Our results demonstrate the effectiveness of the FBC method in improving performance in terms of reduced retrieval time and optimized network resource utilization. Through theoretical evaluations, we provide insights into the benefits of using data popularity as a key factor in cache placement decisions, particularly in the context of NDN architecture.