Radio Frequency Identification Network Planning Using Ascendant Hierarchical Clustering Algorithm

Abstract

Radio Frequency Identification (RFID) is a suitable technology for several application scenarios. However, it faces many issues that need to be addressed. RFID Network Planning (RNP) is one of these challenges, which is studied in this paper. It consists in defining the optimal placement of RFID readers and their communication range. In this study, the RNP issue is considered as a clustering problem. Therefore, it is solved using Ascendant Hierarchical Clustering algorithm (AHC) such that each cluster head represents a reader. The advantage of our proposed approach is that, in addition to optimizing the RNP, it is capable to determine the optimal number of readers needed to get optimal performances. Simulation results demonstrate that the proposed AHC algorithm performs better than two efficient RNP algorithms from the literature: Particle Swarm Optimization (PSO) and Leaders and Followers (LaF) algorithms. Hence, it is observed that AHC algorithm is more efficient, scalable and runs faster than PSO and LaF.