A Formal Energy Consumption Analysis to Secure Cluster-Based WSN: A Case Study of Multi-Hop Clustering Algorithm Based on Spectral Classification Using Lightweight Blockchain

Wireless Sensors Networks are integrating human daily life at a fast rate. Applications cover a wide range of fields, including home security, agriculture, climate change, fire prevention, and so on and so forth. If WSN were initially flat networks, hierarchical, or cluster-based networks have been...

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Published in:Sensors (Basel, Switzerland) Vol. 22; no. 20; p. 7730
Main Authors: Ebobissé Djéné, Yves Frédéric, El Idrissi, Mohammed Sbai, Tardif, Pierre-Martin, Jorio, Ali, El Bhiri, Brahim, Fakhri, Youssef
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.10.2022
MDPI
Subjects:
Algorithms
Analysis
Blockchain
Case studies
Classification
Climatic changes
Clustering
Cryptography
energy
Energy consumption
Energy efficiency
Energy management systems
Energy use
Fire prevention
security
Security management
wireless sensors network
ISSN:1424-8220, 1424-8220
Online Access:Get full text
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Summary:Wireless Sensors Networks are integrating human daily life at a fast rate. Applications cover a wide range of fields, including home security, agriculture, climate change, fire prevention, and so on and so forth. If WSN were initially flat networks, hierarchical, or cluster-based networks have been introduced in order to achieve a better performance in terms of energy efficiency, topology management, delay minimization, load balancing, routing techniques, etc. As cluster-based algorithms proved to be efficient in terms of energy balancing, security has been of less importance in the field. Data shared by nodes in a WSN can be very sensitive depending on the field of application. Therefore, it is important to ensure security at various levels of WSN. This paper proposes a formal modeling of the energy consumed to secure communications in a cluster-based WSN in general. The concept is implemented using the Proof of Authentication (POAh) paradigm of blockchain and applied to a Multi-hop Clustering Algorithm based on spectral classification. The studied metrics are residual energy in the network, the number of alive nodes, first and last dead node.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s22207730