Study on AdaBoost-based link quality prediction mechanism

Jian SHU; Man-lan LIU; Wei ZHENG

doi:10.11959/j.issn.1000-436x.2017233

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Study on AdaBoost-based link quality prediction mechanism

Papers | 更新时间：2024-06-05

- Study on AdaBoost-based link quality prediction mechanism
- Journal on Communications Vol. 38, Issue Z1, Pages: 39-45(2017)
- 作者机构：
  
  1. 南昌航空大学软件学院，江西南昌330063
  2. 南昌航空大学信息工程学院，江西南昌 330063
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61363015);The National Natural Science Foundation of China(61762065);The National Natural Science Foundation of China(61501217);The Natural Science Foundation of Jiangxi Province(20171BAB202009);The Natural Science Foundation of Jiangxi Province(20171ACB20018)
- DOI：10.11959/j.issn.1000-436x.2017233
  CLC： TP393
- Online First：2017-10，
  
  Published：25 October 2017
- 稿件说明：
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Jian SHU, Man-lan LIU, Wei ZHENG. Study on AdaBoost-based link quality prediction mechanism[J]. Journal on Communications, 2017, 38(Z1): 39-45.
DOI：

Jian SHU, Man-lan LIU, Wei ZHENG. Study on AdaBoost-based link quality prediction mechanism[J]. Journal on Communications, 2017, 38(Z1): 39-45. DOI： 10.11959/j.issn.1000-436x.2017233.

摘要

在无线传感器网络中，节点所在环境复杂多变导致其通信链路质量的不可靠，若能提前感知链路质量信息，则能很大程度上降低网络中节点的额外能量消耗。在分析现有链路质量预测方法的基础上，提出基于AdaBoost的链路质量预测机制。通过收集多个实验场景下的链路质量样本，采用基于密度的无监督聚类算法对训练样本划分链路质量等级；采用以支持向量机为弱分类器的 AdaBoost 算法，构建链路质量预测机制。实验结果表明，所提预测机制具有较高的预测精度。

Abstract

The link quality was vulnerable to the complexity environment in wireless sensor network.Obtaining link quality information in advance could reduce energy consumption of nodes.After analyzing the existing link quality prediction methods

AdaBoost-based link quality prediction mechanism was put forward.Link quality samples in deferent scenarios were collected.Density-based unsupervised clustering algorithm was employed to classify training samples into deferent link quality levels.The AdaBoost with SVM-based component classifiers was adopted to build link quality prediction mechanism.Experimental results show that the proposed mechanism has better prediction precision.

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references

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