Affiliation:
1. School of Automation, Guangdong University of Technology, Guangzhou 510006, Guangdong, P. R. China
2. School of Integrated Circuits, Guangdong University of Technology, Guangzhou 510006, Guangdong, P. R. China
Abstract
In RFID systems, many anti-collision algorithms, driven by the concept of rescheduling the response sequence between the reader and unidentified tags, have been put forward to solve tag collision problem, including ALOHA-based, tree-based and hybrid algorithms. In this paper, we propose a novel RFID anti-collision algorithm called EAQ-CBB, which adopts three main approaches: tag population estimation based on collided bit detection method, optimal partitions and trimmed query tree based on the strategy of collided block bit-mapping (QTCBB). The relatively accurate estimation of tag backlog and optimal partition ensure a great reduction of collisions in the initial phase. For each collided partition, a QTCBB process is introduced immediately, which eliminates all the empty slots and significantly reduces the collided slots. Simulation results show that EAQ-CBB performs good stability and scalability when the key parameters change. Compared with the existing algorithms, such as DFSA, QTI, T-GDFSA and CT, EAQ-CBB outperforms the others with high system throughput, low normalized latency and low normalized overhead at a low cost of energy, which makes it easier to be used widely in the efficient-aware and energy-aware applications.
Funder
National Key R&D Program of China
National Natural Science Foundation of China
Guangdong Province Foundation
Publisher
World Scientific Pub Co Pte Ltd
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Software