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An Information Entropy Based Event Boundary Detection Algorithm in Wireless Sensor Networks

Article dans une revue avec comité de lecture
Author
WU, Huafeng
268364 Shanghai Maritime University
MENG, Qingshun
268364 Shanghai Maritime University
XIAN, Jiangfeng
268364 Shanghai Maritime University
MEI, Xiaojun
268364 Shanghai Maritime University
ccCLARAMUNT, Christophe
13094 Institut de Recherche de l'Ecole Navale [IRENAV]
CAO, Junkuo
461061 Hainan Normal University [Haikou, China]

URI
http://hdl.handle.net/10985/20172
DOI
10.3390/sym11040537
Date
2019
Journal
Symmetry

Abstract

Wireless Sensor Networks (WSNs) have been extensively applied in ecological environment monitoring. Typically, event boundary detection is an effective method to determine the scope of an event area in large-scale environment monitoring. This paper proposes a novel lightweight Entropy based Event Boundary Detection algorithm (EEBD) in WSNs. We first develop a statistic model using information entropy to figure out the probability that a sensor is a boundary sensor. The EEBD is independently executed on each wireless sensor in order to judge whether it is a boundary sensor node, by comparing the values of entropy against the threshold which depends on the boundary width. Simulation results demonstrate that the EEBD is computable and offers valuable detection accuracy of boundary nodes with both low and high network node density. This study also includes experiments that verify the EEBD which is applicable in a real ocean environmental monitoring scenario using WSNs.

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