Building the Data Association Network of Sensors in the Internet of Things

被引：2

作者：

Wei, Xiao ^{[1
]}

Li, Qing ^{[2
]}

Ye, Feiyue ^{[3
]}

Zhang, Jun ^{[3
]}

Bie, Rongfang ^{[4
]}

机构：

[1] Shanghai Univ, Sch Comp Engn & Sci, Shanghai, Peoples R China

[2] City Univ Hong Kong, Dept Comp Sci, Hong Kong, Hong Kong, Peoples R China

[3] Shanghai Univ, Sch Comp Engn & Sci, Shanghai 200072, Peoples R China

[4] Beijing Normal Univ, Beijing 100875, Peoples R China

来源：

AUTOMATIKA | 2013年 / 54卷 / 04期

基金：

美国国家科学基金会;

关键词：

Data Mining on IoT; Data Association of Sensors; Data Association Network of Sensors;

D O I：

10.7305/automatika.54-4.419

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In the Internet of Things, wireless sensor networks (WSN) is in charge of gathering and transferring environment data. It is an essential work to mine data semantic in WSN in the data derived from sensors to improve the WSN. This paper proposes the Data Association Network of sensors (DAN) to organize the mined association semantic relations among sensors into an effective form. Because DAN holds the rich data semantic of WSN, it can improve WSN in some aspects, such as detecting the abnormal sensors, simulating the data of faulty sensors, or optimizing the topology of WSN. Experimental results show that the proposed method can mine the associated relations among sensor nodes effectively, and the DAN is helpful in solving some problems of WSN.

引用

页码：459 / 470

页数：12