传感技术学报2017，Vol.30Issue(2)：306-312,7.DOI:10.3969/j.issn.1004-1699.2017.02.024
基于异常数据驱动的WSN簇内数据融合方法
A Data Aggregation Method Based on Abnormal Data-Drivenin Clusters of Wireless Sensor Networks
摘要
Abstract
Aiming at the deficiency of traditional data aggregation methods,a new aggregation method based on abnormal data-driven is proposed by introducing the mechanism of data-driven.In the phase of data acquisition,the sensor nodes only send the abnormal data to cluster head when exceptional event occurs randomly,this can effectively reduce the network traffic.In the phase of data aggregation for cluster head,the support matrix is constructed between sensors,those monitoring data which has lower support values will be eliminated,only the higher support value data is aggregated by cluster head with the method of optimal weight,thus ensuring the accuracy and validity of aggregation results.The simulation experiments show that,compared with the mean value method and the self-adaptive weighted aggregation method,the proposed method can effectively remove redundant information in the period of data transmission,which has obvious advantages in aggregation precision and energy consumption.关键词
无线传感器网络/异常数据驱动/数据融合/支持度矩阵Key words
wireless sensor networks/abnormal data-driven/data aggregation/support matrix分类
信息技术与安全科学引用本文复制引用
谭德坤,付雪峰,赵嘉,涂振宇..基于异常数据驱动的WSN簇内数据融合方法[J].传感技术学报,2017,30(2):306-312,7.基金项目
国家自然科学基金项目(61261039) （61261039）
江西省科技支撑计划项目(20142BBE50040,20142BBG70034,20151BBE50077) （20142BBE50040,20142BBG70034,20151BBE50077）
