Error Beacon Filtering Algorithm Based on K-Means Clustering for Underwater Wireless Sensor Networks

被引：0

作者：

Liu, Linfeng ^{[1
,2
]}

Du, Jingli ^{[2
]}

Guo, Dongyue ^{[2
]}

机构：

[1] Southeast Univ, Minist Educ, Lab Comp Network & Informat Integrat, Nanjing 211189, Jiangsu, Peoples R China

[2] Nanjing Univ Posts & Telecommun, Sch Comp Sci & Engn, Nanjing 210003, Jiangsu, Peoples R China

来源：

PROCEEDINGS OF 2016 8TH IEEE INTERNATIONAL CONFERENCE ON COMMUNICATION SOFTWARE AND NETWORKS (ICCSN 2016) | 2016年

关键词：

underwater wireless sensor networks; errorbeacon filtering; localization algorithm; K-means clustering;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Due to the highly hostile and unpredictable underwater environments, some beacon nodes in Underwater Wireless Sensor Networks (UWSNs) tend to move or be damaged. Therefore, the unknown nodes will be positioned with larger error, which abases the value of data collected by sensor nodes. In order to solve the beacon error problem, this paper proposes an error beacon filtering algorithm based on K-means clustering. Firstly, the position of each beacon is calculated by an improved trilateration method, and then the beacon with the maximum positioning error is filtered out through K-means clustering algorithm. Simulation results suggest that this algorithm can detect almost all error beacons effectively.

引用

页码：435 / 438

页数：4

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