Segmented Bloom Filter Based Missing Tag Detection for Large-Scale RFID Systems With Unknown Tags

Radio frequency identification (RFID) is one of the key technologies of the Internet of Things, which has been widely applied to many scenarios, such as tracking, warehouse monitoring, and vehicular social network. In such applications, some of the objects are attached with low-cost tags, which need to be monitored carefully. Hence, the object monitoring can be achieved by missing tag detection in the RFID system. However, unknown tags, whose IDs are not known by the reader in prior, may exist in the system to interfere the missing tag detection and reduce the time efficiency. In this paper, we propose a segmented bloom filter-based missing tag detection scheme called SBFMD, which consists of two phases, i.e., deactivation phase and detection phase. The idea behind the proposed SBFMD scheme is to eliminate the useless slots away from the bloom filter-based frame to improve the detection efficiency. We theoretically optimize the parameters of the proposed SBFMD scheme to maximize the efficiency with a required reliability. Extensive simulations are conducted to evaluate the performance of the proposed SBFMD scheme, the results of which validate its effectiveness.