Performance-effective and low-complexity redundant reader detection in wireless RFID networks

Abstract

The problems of redundant RFID reader detection and coverage have instigated researchers to propose different optimization heuristics due to the rapid advance of technologies in large-scale RFID systems. In this paper, we present a layered elimination optimization (LEO) which is an algorithm-independent technique aims to detect maximum amount of redundant readers that could be safely removed or turned off with preserving original RFID network coverage. A significant improvement of the LEO scheme is that amount of write-to-tag operations could be largely reduced during the redundant reader identification phase. Moreover, LEO is a distributed approach which does not need to collect global information for centralizing control, leading to no communications or synchronizations among RFID readers. To evaluate the performance of the proposed techniques, we have implemented the LEO technique along with other methods. Both theoretical analysis and experimental results show that the LEO is reliable, effective, and efficient. The proposed techniques can provide reliable performance with detecting higher redundancy and has lower algorithm overheads.