DocumentCode :
653214
Title :
A Progressive Population Estimation Based Binary Query Tree Protocol for Efficient RFID Tag Collision Resolution
Author :
Xin-Qing Yan ; Yi-Su Wang ; Yang Liu ; Xue-Mei Liu
fYear :
2013
fDate :
20-23 Aug. 2013
Firstpage :
564
Lastpage :
571
Abstract :
RFID technology enables the automatic identification of physical items and acts as a bridge between the physical world and the cyber space. But tag collision remains a key challenge that affects the universal deployment of the RFID system. For the efficient resolution of collisions caused by passive memory-less RFID tags, this paper proposes the progressive estimation of tag population and an enhanced binary query tree protocol. In this protocol, after an idle or a successful query, according to the number of tag already identified and the binary query string broadcasted by the reader, the overall population of tags near the reader is estimated, and the optimal binary string for the reader to broadcast in the next query will be calculated. This process is performed repeatedly until all collisions are resolved. Theoretical analysis and numeric simulation are performed, it is verified that this protocol performs better in terms of throughput, message complexity and time latency.
Keywords :
protocols; radiofrequency identification; trees (mathematics); RFID tag collision resolution; binary query string; binary query tree protocol; message complexity; optimal binary string; passive memory-less RFID tags; progressive population estimation; radiofrequency identification; tag population; time latency; Estimation; Open area test sites; Protocols; Radiofrequency identification; Sociology; Statistics; Throughput;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE Cyber, Physical and Social Computing
Conference_Location :
Beijing
Type :
conf
DOI :
10.1109/GreenCom-iThings-CPSCom.2013.107
Filename :
6682121
Link To Document :
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