ANN FOR NODE LOCALIZATION INWIRELESS SENSOR NETWORK

International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering

article

ShikhaBhardwaj¹ 

[1] Dept. of IT, University school of Information and Communication Technology, Guru Gobind Singh Indraprastha University

关键词: Wireless Sensor Network;    Localization;    Backpropagation algorithm;    Neural network;    Resilient Backpropagation;    Levenberg-Marquardt;    Beacon nodes;    anchor nodes;    Artificial neural network.;   

来源: Research & Reviews

【 摘 要 】

With the increasing use and application of Wireless Sensor Networks (WSN), need has arisen to make them more efficient in a cost effective way. An important area which can bring efficiency to WSNs is the localization process by which the sensor nodes in the network can identify their own location in the overall network. The objective of this paper is to study and test the use of Artificial Neural Networks (ANNs) as a method of localization in WSNs. This is achieved by using Backpropagation algorithm (BPN) based on multilayer perceptron (MLP) neural networks to carry out the localization process. The network consisting of sensor nodes is initially trained using training algorithms namely Levenberg-Marquardt and Resilient Backpropagation. The network is then tested with a new independent set of data to prove the effectiveness of proposed model. In the paper, other variables like number of anchor nodes, neurons in hidden layers etc. which impact the efficiency of the network in localisation process are also analysed.

【 授权许可】

Unknown