TY - GEN
T1 - Performance study of anti-collision algorithms for EPC-C1 Gen2 RFID protocol
AU - Lee, Joon Goo
AU - Hwang, Seok Joong
AU - Kim, Seon Wook
N1 - Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2008
Y1 - 2008
N2 - Recently RFID systems have become a very attractive solution for a supply chain and distribution industry to trace a position or delivery status of goods. RFID has many advantages over barcode and vision recognition systems, but there are still many problems to be solved. One of the important issues is channel efficiency. To get higher efficiency, a reader uses an anti-collision algorithm. In this paper, we characterize a set of anti-collision algorithms based on a framed slotted ALOHA protocol when using EPC-C1 Gen2 protocol with different frame sizes. Additionally, we propose a simple and effective algorithm which called DDFSA. The proposed algorithm outperformed a conventional Dynamic Framed Slotted ALOHA with a threshold method by 14.6% on average. We also explain why Gen2 has a good channel efficiency in bad environment.
AB - Recently RFID systems have become a very attractive solution for a supply chain and distribution industry to trace a position or delivery status of goods. RFID has many advantages over barcode and vision recognition systems, but there are still many problems to be solved. One of the important issues is channel efficiency. To get higher efficiency, a reader uses an anti-collision algorithm. In this paper, we characterize a set of anti-collision algorithms based on a framed slotted ALOHA protocol when using EPC-C1 Gen2 protocol with different frame sizes. Additionally, we propose a simple and effective algorithm which called DDFSA. The proposed algorithm outperformed a conventional Dynamic Framed Slotted ALOHA with a threshold method by 14.6% on average. We also explain why Gen2 has a good channel efficiency in bad environment.
UR - http://www.scopus.com/inward/record.url?scp=58049126130&partnerID=8YFLogxK
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U2 - 10.1007/978-3-540-89524-4_52
DO - 10.1007/978-3-540-89524-4_52
M3 - Conference contribution
AN - SCOPUS:58049126130
SN - 354089523X
SN - 9783540895237
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 523
EP - 532
BT - Information Networking
PB - Springer Verlag
T2 - 21st International Conference on Information Networking, ICOIN 2007
Y2 - 23 January 2007 through 25 January 2007
ER -