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Research Article | Open Access

The use of Analytical Hierarchy Process in sensor-based networks for security-aware congestion control

Divya Pandey( )Vandana Kushwaha
Institute of Science, Banaras Hindu University, Varanasi-221005, India
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Abstract

Network congestion may occur naturally or intentionally caused by selfish nodes. Existing congestion control techniques designed by researchers for sensor-based networks have primarily focused on natural modes of congestion occurrence and ignored malevolent nodes' potential for purposeful congestion-like scenario creation. In light of this fact, a security attack-resistant congestion control method that takes into account both possible sources of congestion in sensor nodes has been developed. So firstly, a trust-based technique has been developed to get rid of selfish nodes' intentional attempts to cause congestion. After the elimination of malicious nodes, a congestion avoidance method has been applied which tries to prevent the natural way of congestion occurrence. For this purpose, we have applied a multi-criteria decision-making method as there are many factors responsible for congestion occurrence. The remaining energy, node potential value, node load factor, and traffic burst rate have been considered as decision factors. Simulation results show that our Security Aware Congestion Control technique using the AHP method (SACC-AHP) outperforms the existing relevant techniques LEACH, TCEER, TASRP, CARA and SACC in terms of energy efficiency, security, packet delivery ratio and network lifetime.

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Networks and Heterogeneous Media
Pages 244-274

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Cite this article:
Pandey D, Kushwaha V. The use of Analytical Hierarchy Process in sensor-based networks for security-aware congestion control. Networks and Heterogeneous Media, 2023, 18(1): 244-274. https://doi.org/10.3934/nhm.2023009

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Received: 31 October 2022
Revised: 02 December 2022
Accepted: 04 December 2022
Published: 15 March 2023
©2023 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)