Universiti Teknologi Malaysia Institutional Repository

ANN based novel approach to detect node failure in wireless sensor network

Perumal, Sundresan and Tabassum, Mujahid and Narayana, Ganthan and Ponnan, Suresh and Chakraborty, Chinmay and Mohanan, Saju and Basit, Zeeshan and Quasim, Mohammad Tabrez (2021) ANN based novel approach to detect node failure in wireless sensor network. Computers, Materials and Continua, 69 (2). pp. 1447-1462. ISSN 1546-2218


Official URL: http://dx.doi.org/10.32604/cmc.2021.014854


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.

Item Type:Article
Uncontrolled Keywords:AODV, artificial intelligence, artificial neural network, mahalanobis distance, node failure, throughput, wireless sensor network
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Razak School of Engineering and Advanced Technology
ID Code:96592
Deposited By: Yanti Mohd Shah
Deposited On:31 Jul 2022 09:18
Last Modified:31 Jul 2022 09:18

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