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
Efficient Object Identification with Passive RFID Tags
Pervasive '02 Proceedings of the First International Conference on Pervasive Computing
Batch conflict resolution algorithm with progressively accurate multiplicity estimation
Proceedings of the 2004 joint workshop on Foundations of mobile computing
An Enhanced Dynamic Framed Slotted ALOHA Algorithm for RFID Tag Identification
MOBIQUITOUS '05 Proceedings of the The Second Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services
Tree Slotted Aloha: a New Protocol for Tag Identification in RFID Networks
WOWMOM '06 Proceedings of the 2006 International Symposium on on World of Wireless, Mobile and Multimedia Networks
Efficient Collision-Resilient RFID Tag Identification using Balanced Incomplete Block Design Code
CIT '06 Proceedings of the Sixth IEEE International Conference on Computer and Information Technology
Tag-Splitting: Adaptive Collision Arbitration Protocols for RFID Tag Identification
IEEE Transactions on Parallel and Distributed Systems
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Reading efficiency is one of the key factors to evaluate Radio Frequency Identification (RFID) systems. For the system using multi-branch protocols, the performance would be better if the tags are properly divided into multiple groups. This paper firstly gives the closed-form of system efficiency for binary tree algorithm. Based on the theoretical analysis, the optimal branches number is derived. An efficient multibranch tree (EMBT) algorithm is proposed subsequently, along with a tag number estimation algorithm and performance evaluation. Both theoretical analysis and simulation results indicate that multi-branch tree algorithm has better performance than the conventional binary tree algorithm. System identification efficiency of the proposed method can achieve above 45%, while that of the binary tree algorithm is only 34.8%.