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ANN Based Novel Approach to Detect Node Failure in Wireless Sensor Network.

Authors :
Perumal, Sundresan
Tabassum, Mujahid
Narayana, Ganthan
Ponnan, Suresh
Chakraborty, Chinmay
Mohanan, Saju
Basit, Zeeshan
Quasim, andMohammad Tabrez
Source :
Computers, Materials & Continua; 2021, Vol. 69 Issue 2, p1447-1462, 16p
Publication Year :
2021

Abstract

A wireless sensor network (WSN) consists of several tiny sensor nodes to monitor, collect, and transmit the physical information from an environment through the wireless channel. The node failure is considered as one of themain issues in theWSN which creates higher packet drop, delay, and energy consumption during the communication. Although the node failure occurred mostly due to persistent energy exhaustion during transmission of data packets. In this paper, Artificial Neural Network (ANN) based Node Failure Detection (NFD) is developed with cognitive radio for detecting the location of the node failure. The ad hoc on-demand distance vector (AODV) routing protocol is used for transmitting the data from the source node to the base station. Moreover, the Mahalanobis distance is used for detecting an adjacent node to the node failure which is used to create the routing path without any node failure. The performance of the proposed ANN-NFD method is analysed in terms of throughput, delivery rate, number of nodes alive, drop rate, end to end delay, energy consumption, and overhead ratio. Furthermore, the performance of the ANN-NFD method is evaluated with the header to base station and base station to header (H2B2H) protocol. The packet delivery rate of the ANN-NFD method is 0.92 for 150 nodes that are high when compared to the H2B2H protocol. Hence, the ANN-NFD method provides data consistency during data transmission under node and battery failure. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15462218
Volume :
69
Issue :
2
Database :
Complementary Index
Journal :
Computers, Materials & Continua
Publication Type :
Academic Journal
Accession number :
151640374
Full Text :
https://doi.org/10.32604/cmc.2021.014854