Open AccessGen2‐Based Tag Anti‐collision Algorithms Using Chebyshev's Inequality and Adjustable Frame Size
Author(s) -
Fan Xiao,
Song InChan,
Chang KyungHi,
Shin DongBeom,
Lee HeyungSub,
Pyo CheolSig,
Chae JongSuk
Publication year - 2008
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.08.1308.0098
Subject(s) - aloha , algorithm , computer science , identification (biology) , collision , chebyshev filter , throughput , frame (networking) , chebyshev's inequality , radio frequency identification , mathematics , inequality , linear inequality , computer network , telecommunications , mathematical analysis , botany , computer security , kantorovich inequality , wireless , computer vision , biology
Arbitration of tag collision is a significant issue for fast tag identification in RFID systems. A good tag anti‐collision algorithm can reduce collisions and increase the efficiency of tag identification. EPCglobal Generation‐2 (Gen2) for passive RFID systems uses probabilistic slotted ALOHA with a Q algorithm, which is a kind of dynamic framed slotted ALOHA (DFSA), as the tag anti‐collision algorithm. In this paper, we analyze the performance of the Q algorithm used in Gen2, and analyze the methods for estimating the number of slots and tags for DFSA. To increase the efficiency of tag identification, we propose new tag anti‐collision algorithms, namely, Chebyshev's inequality, fixed adjustable framed Q, adaptive adjustable framed Q, and hybrid Q. The simulation results show that all the proposed algorithms outperform the conventional Q algorithm used in Gen2. Of all the proposed algorithms, AAFQ provides the best performance in terms of identification time and collision ratio and maximizes throughput and system efficiency. However, there is a tradeoff of complexity and performance between the CHI and AAFQ algorithms.