Probabilistic counting algorithms for data base applications
Journal of Computer and System Sciences
Efficient memoryless protocol for tag identification (extended abstract)
DIALM '00 Proceedings of the 4th international workshop on Discrete algorithms and methods for mobile computing and communications
Computer Networks
LANDMARC: indoor location sensing using active RFID
Wireless Networks - Special issue: Pervasive computing and communications
RFID Technology and Applications
IEEE Pervasive Computing
Adaptive splitting protocols for RFID tag collision arbitration
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
Energy-Aware Tag Anti-Collision Protocols for RFID Systems
PERCOM '07 Proceedings of the Fifth IEEE International Conference on Pervasive Computing and Communications
Efficient storage scheme and query processing for supply chain management using RFID
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Sherlock: automatically locating objects for humans
Proceedings of the 6th international conference on Mobile systems, applications, and services
Counting RFID tags efficiently and anonymously
INFOCOM'10 Proceedings of the 29th conference on Information communications
ASAP: Scalable Identification and Counting for Contactless RFID Systems
ICDCS '10 Proceedings of the 2010 IEEE 30th International Conference on Distributed Computing Systems
Fast Capture—Recapture Approach for Mitigating the Problem of Missing RFID Tags
IEEE Transactions on Mobile Computing
Tree algorithms for packet broadcast channels
IEEE Transactions on Information Theory
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Radio Frequency Identification (RFID) systems are widely used in various applications such as supply chain management, inventory control, and object tracking. Identifying RFID tags in a given tag population is the most fundamental operation in RFID systems. While the Tree Walking (TW) protocol has become the industrial standard for identifying RFID tags, little is known about the mathematical nature of this protocol and only some ad-hoc heuristics exist for optimizing it. In this paper, first, we analytically model the TW protocol, and then using that model, propose the Tree Hopping (TH) protocol that optimizes TW both theoretically and practically. The key novelty of TH is to formulate tag identification as an optimization problem and find the optimal solution that ensures the minimal average number of queries. With this solid theoretical underpinning, for different tag population sizes ranging from 100 to 100K tags, TH significantly outperforms the best prior tag identification protocols on the metrics of the total number of queries per tag, the total identification time per tag, and the average number of responses per tag by an average of 50%, 10%, and 30%, respectively, when tag IDs are uniformly distributed in the ID space, and of 26%, 37%, and 26%, respectively, when tag IDs are non-uniformly distributed.