A new perceptron based neural-network algorithm to enhance the scheduling performance of safety-critical WSNs of increased dependability

Conference paper


Al-Nader, I, Lasebae, A. and Raheem, R. 2024. A new perceptron based neural-network algorithm to enhance the scheduling performance of safety-critical WSNs of increased dependability. So In, C., Londhe, N.D., Bhatt, N. and Kitsing, M. (ed.) 8th World Conference on Information Systems for Business Management. Bangkok, Thailand 07 - 08 Sep 2023 Springer. pp. 347-366 https://doi.org/10.1007/978-981-99-8612-5_28
TypeConference paper
TitleA new perceptron based neural-network algorithm to enhance the scheduling performance of safety-critical WSNs of increased dependability
AuthorsAl-Nader, I, Lasebae, A. and Raheem, R.
Abstract

Wireless Sensor Networks (WSNs) are embedded systems consisting of multiple distributed Sensor Nodes and usually one or more Base Stations (BSs), placed within an area of interest, to monitor and detect given behaviours and changes. Nowadays, WSNs are widely used in Safety-Critical systems where their dependability requirements are determined by the correct operations of the three primary properties: Connectivity, Coverage, and Lifetime of the network. These properties have been mostly addressed independently of each other due to the complexity of addressing them simultaneously within a networked environment. This paper proposes a Perceptron-based Artificial Neural Network (ANN) analyser to analyse the performance of the Scheduling algorithms (e.g., where nodes alternate between awake (ON) and sleep (OFF) states) in WSNs using a MATLAB simulation environment. This approach uses a neural network to learn, train, and test the performance of such algorithms, to better the overall dependability of the network. The simulation results show possible ways to improve the lifetime of nodes using a more dynamic connectivity /coverage strategy. In particular, nodes that switched ON more than four times were identified and classified. This has the benefit of improving network lifetime and hence its service availability and reliability attributes (dependability) by balancing the workload or the sleep-schedule of those nodes, the network’s lifetime increases by avoiding unnecessarily depleting nodes’ energy.

KeywordsInternet of Things (IoT); WSN; dependability; WSN optimisation; WSN duty cycle; (Artificial Intelligence) AI performance analysis
Sustainable Development Goals9 Industry, innovation and infrastructure
Middlesex University ThemeSustainability
Conference8th World Conference on Information Systems for Business Management
Page range347-366
Proceedings TitleInformation Systems for Intelligent Systems: Proceedings of ISBM 2023
SeriesSmart Innovation, Systems and Technologies (SIST)
EditorsSo In, C., Londhe, N.D., Bhatt, N. and Kitsing, M.
ISSN2190-3018
Electronic2190-3026
ISBN
Hardcover9789819986118
Paperback9789819986149
Electronic9789819986125
PublisherSpringer
Publication dates
Online27 Feb 2024
Print27 Feb 2024
Publication process dates
Accepted29 Jun 2023
Deposited11 Dec 2023
Output statusPublished
Accepted author manuscript
File Access Level
Open
Copyright Statement

This version of the article has been accepted for publication, and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-ma...), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://link.springer.com/book/9789819986118

Digital Object Identifier (DOI)https://doi.org/10.1007/978-981-99-8612-5_28
Web address (URL) of conference proceedingshttps://doi.org/10.1007/978-981-99-8612-5
LanguageEnglish
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