基于AdaBoost的链路质量预测机制研究  

Study on AdaBoost-based link quality prediction mechanism

作　　者：舒坚[1] 刘满兰 郑巍[1] 

机构地区：[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

出　　处：《通信学报》2017年第A01期39-45,共7页Journal on Communications

基　　金：国家自然科学基金资助项目(No.61363015;No.61762065;No.61501217);江西省自然科学重点基金资助项目(No.20171BAB202009;No.20171ACB20018)~~

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。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 pre-diction 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 pre-diction mechanism. Experimental results show that the proposed mechanism has better prediction precision.

关 键 词：无线传感网络 链路质量预测 ADABOOST 链路质量等级划分 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]