Dynamic RFID Network Optimization Using a Self-adaptive Bacterial Foraging Algorithm

Abstract

Due to the low cost and simple deployment, radio frequency identification (RFID) systems are used in a variety of applications to uniquely identify physical objects. However, a number of critical design issues relating to dynamic determination of the optimal placement of RFID readers remain unresolved. In this paper, we address two important problems associated with reader location in RFID networks: (i) reader collision avoidance; (ii) optimal tag coverage. This paper, therefore, aims to use a successful swarm intelligence technique called self-adaptive bacterial foraging optimization (SABFO) to optimize both the reader-to-reader interference and tag coverage problems in RFID networks. The optimization results are also compared with the classical bacterial foraging optimization (BFO) algorithm. Numerical results for a RFID network case with ten readers have been presented to demonstrate the performance of the SABFO algorithm.