Software defined content popularity estimation for wireless D2D caching networks

Abstract

In this work, we are going to find a way to estimate content popularity in clustered networks. Since software-defined methods make planning more automatic and flexible, in this paper we take the help of software-defined methods for content estimation. For this purpose, the content popularity estimation algorithm is implemented by the base station located in the control plane. At the data plane level, there are users and among the users, there are several helper users who use the cache content in their device both to benefit other users and reduce base station traffic. First, we cluster the helpers using clustering methods. Then we present an optimal algorithm to estimate content popularity in each cluster, and finally, in a cellular network with the ability to communicate using a D2D connection we use cache placement to maximize offload traffic. Evaluations show that cache placement based on the proposed content popularity estimation algorithm increases the hit rate and offload. © 2023 IEEE.