A novel scheduling algorithm for improved performance of multi-objective safety-critical WSN using spatial self-organizing feature map

Article

Al-Nader, I., Lasebae, A. and Raheem, R. 2024. A novel scheduling algorithm for improved performance of multi-objective safety-critical WSN using spatial self-organizing feature map. Electronics. 13 (1). https://doi.org/10.3390/electronics13010019
TypeArticle
TitleA novel scheduling algorithm for improved performance of multi-objective safety-critical WSN using spatial self-organizing feature map
AuthorsAl-Nader, I., Lasebae, A. and Raheem, R.
Abstract

Technological advances in the internet of things (IoT) allowed a low-cost, yet small sensor device to operate with limited power in a dynamic harsh environment where human intervention is impossible. The wireless sensor network (WSN) is an example of the IoT in which physical devices’ software and sensors can interconnect to provide application services. It is important that such applications be dependable to meet the required quality of service (QoS) and function as expected. Consequently, the multi-objective optimization (MOO) problem in WSNs aims to address the trade-off among coverage, connectivity, and network lifetime requirements. Node scheduling is one approach of many used to optimize energy in WSNs. The contribution of this work is the proposal of a self-organizing feature map (SOFM) to enhance the node scheduling in WSNs. The proposed SOFM node-scheduling algorithm aims to spatially explore the state space domain and obtain an optimal solution. In our experiment, the proposed SOFM node-scheduling algorithm is evaluated against a comparable algorithm, namely the BAT node-scheduling algorithm, via MATLAB simulator. The results showed that the SOFM node-scheduling algorithm outperformed the latter by 27% and 28% for the maximum and minimum coverage, respectively, with similar performance of 99% of connectivity and network lifetime.

KeywordsIoT sensor system; ad hoc sensor network; dependable WSN; smart sensing for safety; scheduling algorithms; real-time systems; QoS in WSN; SOM; SOFM neural networks
Sustainable Development Goals9 Industry, innovation and infrastructure
Middlesex University ThemeSustainability
PublisherMDPI AG
JournalElectronics
ISSN
Electronic2079-9292
Publication dates
Online19 Dec 2023
Print01 Jan 2024
Publication process dates
Submitted28 Oct 2023
Accepted15 Dec 2023
Deposited05 Mar 2024
Output statusPublished
Publisher's version
License
File Access Level
Open
Copyright Statement

© 2023 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/electronics13010019
Web of Science identifierWOS:001139307000001
LanguageEnglish
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