Detection of Coverage Hole Nodes in Wireless Sensor Network using Artificial Intelligence
Mainka1, Khushal Thakur2, Kiran Jot Singh3
1Mainka Nafri, Department of Electronics and Communication Engineering, Chandigarh University, Mohali (Punjab), India.
2Khushal Thakur, Assistant Professor, Department of Electronics and Communication Engineering, Chandigarh University, Mohali (Punjab), India.
3Kiran Jot Singh, P.H.D, Department of Electronics and Communication Engineering, Chandigarh University, Mohali (Punjab), India.
Manuscript received on 05 August 2019 | Revised Manuscript received on 12 August 2019 | Manuscript Published on 26 August 2019 | PP: 603-606 | Volume-8 Issue-9S August 2019 | Retrieval Number: I10950789S19/19©BEIESP | DOI: 10.35940/ijitee.I1095.0789S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Adequate coverage of the sensing field in Wireless sensor networks (WSNs) is critical to many applications. However, when one or more sensor nodes stop working due to energy exhaustion or physical damage, the network may experience overlay vulnerability. This can disrupt network connectivity and hinder performance. Therefore, it must be fixed automatically. To resolve this problem, swarm inspired Artificial Bee Colony (ABC) scheme in addition to the Artificial Neural Network (ANN) approach is used. The aim of ABC is to optimize the shortest path by selecting an appropriate fitness function and then identify holes using ANN. Before the detection of holes, ANN is trained as per the optimized properties of nodes that are as per the genuine nodes and coverage hole repair properties. Therefore during the testing process, ANN compares these properties with the stored properties and then identify the hole repair node. From the experiment, it has been analyzed that the energy consumption up to 23.88% is saved.
Keywords: WSN, Coverage Holes, Mobility, ABC, ANN
Scope of the Article: Adhoc and Sensor Networks