详细信息
文献类型:期刊文献
中文题名:基于RFID的未知标签检测协议研究
英文题名:Research on unknown label detection protocol based on RFID
作者:赖锴[1];米慧超[1]
第一作者:赖锴
机构:[1]河南财经政法大学计算机与信息工程学院
第一机构:河南财经政法大学计算机与信息工程学院
年份:2015
卷号:32
期号:3
起止页码:814-820
中文期刊名:计算机应用研究
外文期刊名:Application Research of Computers
收录:CSTPCD;;北大核心:【北大核心2014】;CSCD:【CSCD_E2015_2016】;
基金:河南省教育厅资助项目(13A120031)
语种:中文
中文关键词:RFID技术;标签;检测;协议;基准算法;运行时间
外文关键词:RFID technology ; tag ; detection ; protocol ; baseline algorithm ; execution time
摘要:RFID技术大大提高了库存管理、目标跟踪、供应链管理等诸多领域的工作效率。在这些应用中,经常需要将新的对象加入到系统中,现有对象经常被放错区域。当这些情况发生时,很有必要把这些标签快速、完整地检测出来。当前的检测技术并不能保证收集到所有未知标签,针对这一问题,给出了一种高效协议,解决了如何在不发射标签标志情况下关闭已知标签,通过比较已知标签预期回答与实际测得回答,阅读器实现已知标签和未知标签的检测。据此,提出了一种无冲突时隙配对技术及多散列时隙选择技术,帮助标签选择最佳时隙与阅读器通信,有效解决了未知标签和已知标签检测间的冲突,显著提高了检测效率。模拟实验结果表明,该算法性能优异,与收集系统中所有标签身份的基准算法相比,最优协议的运行时间平均降低了63%,降低幅度最多可达85%。
The RFID technology greatly improves efficiency of many applications including inventory control, object tracking, and supply chain management. In such applications, it is common that new objects are added into the system or existing ob- jects are misplaced in wrong regions. When this happens, fast and complete identification of such tags is very important. Exi- sting works on unknown tag identification cannot guarantee that all the unknown tags are collected. To solve this problem, this paper proposed an efficient known tag deactivation protocol without transmitting tags' IDs. The reader recognized known tags and unknown tags by comparing the expected replies from known tags with the actual observed replies, and then this paper de- veloped a collision-empty slot paring technique, together with multiple hashing based slot reselections, to help tags select best slots to communicate with the reader. Which efficiently resolve collisions caused by known tags when identifying unknown tags and greatly improve the time efficiency. Simulation results show the superior performance of the proposed protocols : compared with a baseline method which collects IDs of all the tags in the system, the best protocol reduces the execution time by 63% in average and by 85% at most.
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