A Bit-Tracking Knowledge-Based Query Tree for RFID Tag Identification in IoT Systems

• Published in: Sensors (Basel, Switzerland) Vol. 22; no. 9; p. 3323
• Main Authors: Lai, Yuan-Cheng, Chen, Shan-Yung, Hailemariam, Zelalem Legese, Lin, Chih-Chung
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 26.04.2022; MDPI
• Subjects: Algorithms; anti-collision protocol; bit tracking; Communication; Computer Simulation; Decision trees; Efficiency; Heuristic; Internet of Things; Knowledge; Knowledge Bases; knowledge-based; Protocol; query tree; Radio frequency identification; Radio frequency identification (RFID); Radio Frequency Identification Device - methods; RFID; anti-collision protocol; RFID; query tree; knowledge-based; bit tracking
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22093323

In an IoT (Internet of Things) system where each IoT device has one/many RFID tags, there might be many RFID tags. However, when multiple tags respond to the reader’s interrogation at the same time, their signals collide. Due to the collision, the reader must request the colliding tags to retransmit their IDs, resulting in higher communication overhead and longer identification time. Therefore, this paper presents a Bit-tracking Knowledge-based Query Tree (BKQT), which uses two techniques: knowledge, which stores all the tag IDs that can possibly occur, and bit tracking, which allows the reader to detect the locations of the collided bits in a collision slot. BKQT constructs a query tree for all possible tags, called a k-tree, by using knowledge while it constructs bit-collision cases and the corresponding actions for each node in this k-tree by using bit tracking. In the identification process, BKQT traverses this constructed k-tree and thus identifies the colliding tags faster by taking the actions according to the happening bit-collision cases. From the simulation results, BKQT can improve the identification time by 44.3%, 46.4%, and 25.1%, compared with the previous knowledge-based protocols, Knowledge Query Tree (KQT), Heuristic Query Tree (H-QT), Query Tree with Shortcutting and Couple Resolution (QTSC), respectively.