北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2021, Vol. 44 ›› Issue (3): 125-130.doi: 10.13190/j.jbupt.2020-163

• 研究报告 • 上一篇    

基于超限快速决策树的链路质量评估

刘琳岚1, 肖庭忠1, 夏扬2, 舒坚2   

  1. 1. 南昌航空大学 信息工程学院, 南昌 330063;
    2. 南昌航空大学 软件学院, 南昌 330063
  • 收稿日期:2020-09-02 出版日期:2021-06-28 发布日期:2021-06-23
  • 通讯作者: 舒坚(1964-),男,教授,E-mail:shujian@nchu.edu.cn. E-mail:shujian@nchu.edu.cn
  • 作者简介:刘琳岚(1968-),女,教授.
  • 基金资助:
    国家自然科学基金项目(61962037,62062050);江西省自然科学基金项目(20202BABL202039);江西省研究生创新专项项目(YC2020S543)

Link Quality Estimation Based on Extremely Fast Decision Tree

LIU Lin-lan1, XIAO Ting-zhong1, XIA Yang2, SHU Jian2   

  1. 1. School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China;
    2. School of Software, Nanchang Hangkong University, Nanchang 330063, China
  • Received:2020-09-02 Online:2021-06-28 Published:2021-06-23

摘要: 为了准确、快速评估无线传感器网络的链路质量,提出了基于改进超限快速决策树的链路质量评估方法.通过分析不同时间段内物理层参数与包接收率之间的关系,选取接收信号强度指示均值、链路质量指示均值以及信噪比均值作为链路质量参数;采用依据包接收率划分的链路质量等级作为评价指标;基于超限快速决策树评估链路质量,采用基尼指数作为决策节点的启发式度量,并依据决策节点的高度改进决策节点寻找最优属性样本数的计算方法.室内、走廊、停车场3种场景下的实验表明,与模糊逻辑、快速决策树、超限快速决策树等方法相比,提出的方法具有较好的评估准确率和更低的时间复杂度.

关键词: 无线传感器网络, 链路质量评估, 快速决策树, 超限快速决策树

Abstract: To estimate link quality for wireless sensor networks accurately and rapidly, an approach of link quality estimation is proposed based on improved extremely fast decision tree. After analyzing the relationship between the physical parameters and the packet reception rate in different time periods, the received signal strength indicator mean, the link quality indicator mean and the signal to noise ratio mean are selected as the link quality parameters;The evaluation index is determined by the link quality levels divided by packet reception rate. A link quality estimation model is constructed based on extremely fast decision tree, and Gini index is employed as heuristic measure of decision node;the computing method of sample number, with which decision nodes look for the best attributes, is improved in terms of the height of decision node. In scenarios of indoor, corridor and parking lot, the experiment shows that compared with fuzzy logic, very fast decision tree, the earlier extremely fast decision tree etc, the proposed method has better estimation accuracy and lower time complexity.

Key words: wireless sensor networks, link quality estimation, vary fast decision tree, extremely fast decision tree

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