Efficient and robust missing key tag identification for large-scale RFID systems

Radio Frequency Identification(RFID)technology has been widely used to identify missing items.In many applications,rapidly pinpointing key tags that are attached to favorable or valuable items is critical.To realize this goal,interference from ordinary tags should be avoided,while key tags should be efficiently verified.Despite many previous studies,how to rapidly and dynamically filter out ordinary tags when the ratio of ordinary tags changes has not been addressed.Moreover,how to efficiently verify missing key tags in groups rather than one by one has not been explored,especially with varying missing rates.In this paper,we propose an Efficient and Robust missing Key tag Identification(ERKI)protocol that consists of a filtering mechanism and a verification mechanism.Specifically,the filtering mechanism adopts the Bloom filter to quickly filter out ordinary tags and uses the labeling vector to optimize the Bloom filter's performance when the key tag ratio is high.Furthermore,the verification mechanism can dynamically verify key tags according to the missing rates,in which an appropriate number of key tags is mapped to a slot and verified at once.Moreover,we theoretically analyze the parameters of the ERKI protocol to minimize its execution time.Extensive numerical results show that ERKI can accelerate the execution time by more than 2.14compared with state-of-the-art solutions.

Identifying the Unknown Tags in a Large RFID System

Radio frequency identification(RFID) technology has been extensively used in various practical applications, such as inventory management and logistics control, with its outstanding features(e.g. non-line-ofsight reading and fast identification). And in a large RFID system, unknown tag identification uses total execution time as the performance criterion. However, the performance of existing protocols in terms of execution time is not ideal. To get better time efficiency, a novel unknown tag identification protocol(NUTIP) is proposed. The novelty of NUTIP is demonstrated mainly in two aspects: i) NUTIP deactivates some known tags and identifies or labels some unknown tags during its first phase to prevent these tags from interfering unknown tag identification. ii) We optimize the parameter settings to minimize the total execution time. Simulation experiments show that the proposed protocol is far superior to other relevant protocols and suitable for both sparse unknown tags environment and dense unknown tags environment.

Application of Radio Frequency Identification (RFID) in Dairy Information Management

As a kind of brand-new technology, radio frequency identification management, data control and acquisition. This paper introduced food safety system construction, analyzed the advantages and problems in dairy modem suggestions for solution according to the practical situation. （RFID） plays an important role in dairy information tracing and culture function extension of managing breeding technology, and finally put forward some

Bi-slotted Binary Tree Algorithm with Stack for Radio Frequency Identification Tag Anti-Collision

A radio frequency identification (RFID) reader will fail to identify tags if a collision occurs. This paper proposes a bi-slotted binary tree algorithm (BSBTA) with stack for RFID tag anti-collision to improve the performance of binary tree algorithm (BTA). In BSBTA, the reader detects collisions by Manchester code and stores colliding prefixes in a stack. The query is composed of a two-bit prefix and an index value. Following every reader query, there are two timeslots for tags whose pointers and identities (IDs) match the query to respond, one for the tag whose next bit is 0 and the other for the tag with 1 as its next bit. Performance analysis and evaluation are also given. The time complexity and the communication complexity of BTA and BSBTA are derived. The simulation results compare the performance of BSBTA with several related anti-collision algorithms. It is shown that BSBTA outperforms BTA in terms of the average number of responded bits and timeslots for one tag identification.