1. 湖北大学计算机与信息工程学院,湖北,武汉,430062
2. 湖北省教育信息化工程技术研究中心,湖北,武汉,430062
3. 湖北省软件工程工程技术研究中心,湖北,武汉,430062
4. 智慧政务与人工智能应用湖北省工程研究中心,湖北,武汉,430062
5. 湖北大学计算机与信息工程学院,湖北,武汉,430062
6. 湖北省教育信息化工程技术研究中心,湖北,武汉,430062
7. 湖北省软件工程工程技术研究中心,湖北,武汉,430062
8. 智慧政务与人工智能应用湖北省工程研究中心,湖北,武汉,430062
网络出版:2020-08-25,
纸质出版:2020
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宋建华, 何帅, 姚慧. 多阅读器协作的RFID标签树形防碰撞算法[J]. 电子学报, 2020,48(8):1558-1564.
SONG Jian-hua, HE Shuai, YAO Hui. A Multi-Reader Cooperative Tree-Based Anti-Collision Algorithm[J]. Acta Electronica Sinica, 2020, 48(8): 1558-1564.
宋建华, 何帅, 姚慧. 多阅读器协作的RFID标签树形防碰撞算法[J]. 电子学报, 2020,48(8):1558-1564. DOI: 10.3969/j.issn.0372-2112.2020.08.014.
SONG Jian-hua, HE Shuai, YAO Hui. A Multi-Reader Cooperative Tree-Based Anti-Collision Algorithm[J]. Acta Electronica Sinica, 2020, 48(8): 1558-1564. DOI: 10.3969/j.issn.0372-2112.2020.08.014.
在物联网复杂的应用环境中,射频识别技术中的标签碰撞问题作为造成其系统标签识别时间长,通信量大等问题的主要原因,已成为近年来本领域的核心研究热点之一.针对以上问题,本文提出一种多阅读器协作的树形防碰撞算法:在第一阶段,根据位追踪技术能够识别标签碰撞位的特点,阅读器通过判别待识别标签中的碰撞位,从待广播节点中删除已验证的无效节点;在第二阶段的循环广播中,阅读器间通过共享每次的广播的前缀与当次广播结果对自身的树形结构进行不断优化,优化策略是为每一个阅读器分配一个待广播节点队列,通过共享的信息计算待广播节点中含有标签的概率,依据其概率调整队列中待广播节点的优先级,并不断地删除无需广播的节点.在下一轮广播中阅读器选取含有标签概率最大的节点进行广播.仿真实验结果表明:提出的算法的平均标签识别效率达到59.9%,并且在总时隙数量方面有一定优势.
In the complex application environment of the internet of things
tag collision in RFID (radio frequency identification) technology has become one of the core research hotspots in recent years
which is the main reason for the high delay of tag identification and communication cost. To solve the problems above
a MRCT (multi-reader cooperative tree-based algorithm) is proposed in this paper. In the first stage of the algorithm
readers delete part of the invalid nodes according to the advantage of manchester code which can identify the collision bits of tags; In the second stage
readers share the prefix and the current broadcast result in each round of broadcast. The tree structure of the readers is continuously optimized by the information readers shared. The optimization strategy is to allocate a queue of nodes’ priority to be broadcasted for each reader. The probability of tags to be broadcasted is calculated by the shared information. The priority of nodes to be broadcasted is adjusted according to its probability
and the invalid nodes are deleted continuously. In the next broadcast
readers select the node with the highest probability to broadcast. Simulation results show that the average tag recognition efficiency of this algorithm is 59.9%
and MRCT has advantage in total time slots.
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