An efficient and fast kinematics-based algorithm for RFID network planning

Abstract

The Radio Frequency IDentification (RFID) technology is widely used in our life and the RFID Network Planning (RNP) problem has gained increasing attentions. Many algorithms have been proposed to solve this problem, such as genetic algorithm (GA) and particle swarm optimization (PSO) algorithm. However, these algorithms need to know the accurate number of readers before the searching process. In some improved algorithms, the reader elimination operator was designed, such as the Tentative Reader Elimination (TRE) operator, which can adjust the number of readers during the searching process. But these operators have difficult in dealing with large scale problems because of the high computational cost. In this paper, we propose an RFID network planning algorithm with an elimination operator based on kinematics, which is named as curling algorithm for RNP (CA-RNP). We consider each reader as a curling which can slide on the working space. Every tag on the working space generates friction to stop readers. Moreover, we design the reader movement operator and the reader collision operator for searching operation from the viewpoint of kinematics. In the experiments, eight RNP instances are used to verify the performance of CA-RNP. The experimental results show that CA-RNP outperforms GA and PSO, and can find good solutions in a short time.