A Layered Optimization Approach for Redundant Reader Elimination in Wireless RFID Networks

The problem of redundant RFID reader elimination has 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 could be safely removed or turned off with preserving original RFID network coverage. A significant improvement of the LEO scheme is that number of "write-to-tag" operations could be largely reduced during the redundant reader identification phase. Moreover, LEO is a distributed scheme which does not need to collect global information for centralizing control, leading no communications and synchronizations among RFID readers. To evaluate the performance of the proposed techniques, we have implemented the LEO technique along with another redundant reader identification algorithm and other hybrid schemes. In experimental results, the LEO is shown to be effective and provides superior performance in terms of larger number of redundant reader could be detected and with lower algorithm overheads.