[1]任柏翰,张圣杰,石浩森,等.一种自适应的RFID防碰撞算法[J].计算机技术与发展,2018,28(12):67-70.[doi:10.3969/j. issn.1673-629X.2018.12.014]
 REN Bohan,ZHANG Shengjie,SHI Haosen,et al.An Adaptive RFID Anti-collision Algorithm[J].,2018,28(12):67-70.[doi:10.3969/j. issn.1673-629X.2018.12.014]
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一种自适应的RFID防碰撞算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
28
期数:
2018年12期
页码:
67-70
栏目:
智能、算法、系统工程
出版日期:
2018-12-10

文章信息/Info

Title:
An Adaptive RFID Anti-collision Algorithm
文章编号:
1673-629X(2018)12-0067-04
作者:
任柏翰;张圣杰;石浩森;宫婧;
南京邮电大学
Author(s):
REN Bo-hanZHANG Sheng-jieSHI Hao-senGONG Jing
Nanjing University of Posts and Telecommunications,Nanjing 210023,China
关键词:
防碰撞算法射频识别自适应多叉树搜索八叉树
Keywords:
anti-collision algorithmRFIDadaptivemulti-tree searchquadtree
分类号:
TN92
DOI:
10.3969/j. issn.1673-629X.2018.12.014
摘要:
在射频识别的(radio frequency identification,RFID)的应用中,当多个标签同时出现在读写器范围内进行信息传输时,会出现"碰撞"现象,使阅读器无法正常工作。为解决射频识别应用过程中多个标签同时存在引发的碰撞问题,在自适应二四叉树防碰撞算法的基础上,将八叉树引入,提出了一种改进的自适应的二四八叉树算法。该算法通过计算标签的碰撞因子,自适应地选择最优树的叉树,然后进行搜索,从而大大减少了空闲时隙。对改进后的算法进行复杂度分析后,针对不同标签数量的搜索过程,在总时隙数和吞吐率两个方面对算法进行仿真。仿真结果表明,在一定条件下,与自适应的二四叉树相比,改进后的算法可以在减少空闲时隙数的同时提高算法的吞吐率。
Abstract:
In the application of RFID (radio frequency identification),when multiple tags appear in the reader within the scope of infor- mation transmission,there will be“collision”,so that the reader cannot work properly. In order to solve the collision problem caused by the simultaneous existence of multiple tags in the process of radio frequency identification,we propose an improved adaptive quadrangular tree algorithm based on the adaptive quadruple tree anti-collision algorithm. By calculating the collision factor of the tag,the algorithm a- daptively chooses the tree of the optimal tree and then searches for it,which greatly reduces the idle time slot. After analysis of improved algorithm,the simulation is carried out in the total number of timeslots and throughput for the search process of different tags,which shows that the improved algorithm can improve the throughput of the algorithm while reducing its number of idle slots,compared with the adaptive quadtree algorithm.

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更新日期/Last Update: 2018-12-10