A novel bio-inspired bird flocking node scheduling algorithm for dependable safety-critical wireless sensor network systems

Article

Al-Nader, I., Raheem, R. and Lasebae, A. 2025. A novel bio-inspired bird flocking node scheduling algorithm for dependable safety-critical wireless sensor network systems. J - Multidisciplinary Scientific Journal. 8 (2). https://doi.org/10.3390/j8020019
TypeArticle
TitleA novel bio-inspired bird flocking node scheduling algorithm for dependable safety-critical wireless sensor network systems
AuthorsAl-Nader, I., Raheem, R. and Lasebae, A.
Abstract

The Multi-Objective Optimization Problem (MOOP) in Wireless Sensor Networks (WSNs) is a challenging issue that requires balancing multiple conflicting objectives, such as maintaining coverage, connectivity, and network lifetime all together. These objectives are important for a functioning WSN safety-critical applications, whether in environmental monitoring, military surveillance, or smart cities. To address these challenges, we propose a novel bio-inspired Bird Flocking Node Scheduling algorithm, which takes inspiration from the natural flocking behavior of birds migrating over long distance to optimize sensor node activity in a distributed and energy-efficient manner. The proposed algorithm integrates the Lyapunov function to maintain connected coverage while optimizing energy efficiency, ensuring service availability and reliability. The effectiveness of the algorithm is evaluated through extensive simulations, namely MATLAB R2018b simulator coupled with a Pareto front, comparing its performance with our previously developed BAT node scheduling algorithm. The results demonstrate significant improvements across key performance metrics, specifically, enhancing network coverage by 8%, improving connectivity by 10%, and extending network lifetime by an impressive 80%. These findings highlight the potential of bio-inspired Bird Flocking optimization techniques in advancing WSN dependability, making them more sustainable and suitable for real-world WSN safety-critical systems.

KeywordsWSN; MOOP; bird flocking algorithm; BAT node scheduling algorithm; energy efficiency; coverage; sleep cycles
Sustainable Development Goals9 Industry, innovation and infrastructure
Middlesex University ThemeSustainability
PublisherMDPI AG
JournalJ - Multidisciplinary Scientific Journal
ISSN
Electronic2571-8800
Publication dates
Online20 May 2025
Print20 May 2025
Publication process dates
Submitted27 Nov 2024
Accepted16 May 2025
Deposited21 May 2025
Output statusPublished
Publisher's version
License
File Access Level
Open
Copyright Statement

© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Digital Object Identifier (DOI)https://doi.org/10.3390/j8020019
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