An Efficient Approach for Localizing Sensor Nodes in 2D Wireless Sensor Networks Using Whale Optimization-Based Naked Mole Rat Algorithm

Goldendeep Kaur, Kiran Jyoti, Samer Shorman, Anas Ratib Alsoud and Rohit Salgotra ()
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Goldendeep Kaur: Department of Computer Science and Engineering, IK Gujral Punjab Technical University, Jalandhar 144603, Punjab, India
Kiran Jyoti: Department of Computer Science and Engineering, Guru Nanak Dev Engineering College, Ludhiana 141006, Punjab, India
Samer Shorman: College of Arts and Science, Applied Science University, Al Eker P.O. Box 5055, Bahrain
Anas Ratib Alsoud: Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman 19328, Jordan
Rohit Salgotra: Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, 30-059 Kraków, Poland

Mathematics, 2024, vol. 12, issue 15, 1-23

Abstract: Localization has emerged as an important and critical component of research in Wireless Sensor Networks (WSNs). WSN is a network of numerous sensors distributed across broad areas of the world to conduct numerous activities, including sensing the data and transferring it to various devices. Most applications, like animal tracking, object monitoring, and innumerable resources put in the interior as well as outdoor locations, need to identify the position of the occurring incident. The primary objective of localization is to identify the locality of sensor nodes installed in a network so that the location of a particular event can be traced. Different optimization approaches are observed in the work for solving the localization challenge in WSN and assigning the apt positions to undiscovered sensor nodes. This research employs the approach of localizing sensor nodes in a 2D platform utilizing an exclusive static anchor node and virtual anchors to detect dynamic target nodes by projecting these six virtual anchors hexagonally at different orientations and then optimizing the estimated target node co-ordinates employing Whale Optimization-based Naked Mole Rat Algorithm (WONMRA). Moreover, the effectiveness of a variety of optimization strategies employed for localization is compared to the WONMRA strategy concerning localization error and the number of nodes being localized, and it has been investigated that the average error in localization is 0.1999 according to WONMRA and is less than all other optimization techniques.

Keywords: WSN; optimization; localization; WONMRA (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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