Informative counting: fine-grained batch authentication for large-scale RFID systems
Proceedings of the fourteenth ACM international symposium on Mobile ad hoc networking and computing
Understanding RFID counting protocols
Proceedings of the 19th annual international conference on Mobile computing & networking
Maximum Likelihood Approach for RFID Tag Set Cardinality Estimation with Detection Errors
Wireless Personal Communications: An International Journal
Probabilistic Dynamic Framed Slotted ALOHA for RFID Tag Identification
Wireless Personal Communications: An International Journal
Fast tag searching protocol for large-scale RFID systems
IEEE/ACM Transactions on Networking (TON)
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Counting the number of RFID tags (cardinality) is a fundamental problem for large-scale RFID systems. Not only does it satisfy some real application requirements, it also acts as an important aid for RFID identification. Due to the extremely long processing time, slotted ALOHA-based or tree-based arbitration protocols are often impractical for many applications, because tags are usually attached to moving objects and they may have left the readers interrogation region before being counted. Recently, estimation schemes have been proposed to count the approximate number of tags. Most of them, however, suffer from two scalability problems: time inefficiency and multiple-reading. Without resolving these problems, large-scale RFID systems cannot easily apply the estimation scheme as well as the corresponding identification. In this paper, we present the Lottery Frame (LoF) estimation scheme, which can achieve high accuracy, low latency, and scalability. LoF estimates the tag numbers by utilizing the collision information. We show the significant advantages, e.g., high accuracy, short processing time, and low overhead, of the proposed LoF scheme through analysis and simulations.