HHO-LPWSN: Harris Hawks Optimization Algorithm for Sensor Nodes Localization Problem in Wireless Sensor Networks

Sharma, Ravi and Prakash, Shiva (2021) HHO-LPWSN: Harris Hawks Optimization Algorithm for Sensor Nodes Localization Problem in Wireless Sensor Networks. EAI Endorsed Transactions on Scalable Information Systems, 8 (31). e5. ISSN 2032-9407

[img]
Preview
Text
eai.25-2-2021.168807.pdf
Available under License Creative Commons Attribution No Derivatives.

Download (2MB) | Preview

Abstract

Wireless sensor network (WSN) is a prominent technology for remote area monitoring with the assimilation of the Internet of Things (IoT). Over the past decades, sensor node localization has become an essential challenge of WSNs. The sensor indicates localization challenges related to NP-hard problems. Nature-inspired computational intelligence algorithms are used to solve NP-hard problems efficiently for sensor node localization. After the rigorous advanced search in reputable research journals, efficient newly designed Harris Hawks Optimization (HHO) algorithm has not been used to sensor nodes localization until now. Therefore, this paper does and compares the proposed work from the recently available well-known optimization algorithms such as the Salp Swarm Algorithm (SSA), Equilibrium Optimizer (EO), and Grey Wolf Optimizer (GWO). The simulation results of the proposed work showed that it can outperform in terms of average localization error, the number of localized sensor nodes, and computational cost compared to other computational intelligence algorithms.

Item Type: Article
Uncontrolled Keywords: Wireless Sensor Networks, Sensor Nodes, Localization Error, Computational Intelligence, Anchor Nodes, Location Optimization
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
T Technology > T Technology (General)
Depositing User: EAI Editor IV
Date Deposited: 09 Jul 2021 08:31
Last Modified: 09 Jul 2021 08:31
URI: https://eprints.eudl.eu/id/eprint/4393

Actions (login required)

View Item View Item