A collaborated genetic with lion optimization algorithms for improving the quality of forwarding in a vehicular ad-hoc network

Sami Abduljabbar Rashid, Sami Abduljabbar Rashid and Lukman Audah, Lukman Audah and Mustafa Maad Hamdi, Mustafa Maad Hamdi and Mohammed Ahmed Jubair, Mohammed Ahmed Jubair and Mustafa Hamid Hassan, Mustafa Hamid Hassan and Mohammed Salah Abood, Mohammed Salah Abood and Salama A. Mostafa, Salama A. Mostafa (2023) A collaborated genetic with lion optimization algorithms for improving the quality of forwarding in a vehicular ad-hoc network. International Journal of Artificial Intelligence (IJ-AI), 12 (2). pp. 667-677. ISSN 2252-8938

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Official URL: https://doi.org/10.11591/ijai.v12.i2.pp667-677

Abstract

Vehicular ad-hoc network (VANET) is dynamic and it works on various noteworthy applications in intelligent transportation systems (ITS). In general, routing overhead is more in the VANETs due to their properties. Hence, need to handle this issue to improve the performance of the VANETs. Also due to its dynamic nature collision occurs. Up till now, we have had immense complexity in developing the multi-constrained network with high quality of forwarding (QoF). To solve the difficulties especially to control the congestion this paper introduces an enhanced genetic algorithmbased lion optimization for QoF-based routing protocol (EGA-LOQRP) in the VANET network. Lion optimization routing protocol (LORP) is an optimization-based routing protocol that can able to control the network with a huge number of vehicles. An enhanced genetic algorithm (EGA) is employed here to find the best possible path for data transmission which leads to meeting the QoF. This will result in low packet loss, delay, and energy consumption of the network. The exhaustive simulation tests demonstrate that the EGA-LOQRP routing protocol improves performance effectively in the face of congestion and QoS assaults compared to the previous routing protocols like Ad hoc on-demand distance vector (AODV), ant colony optimization-AODV (ACO-AODV) and traffic aware segmentAODV (TAS-AODV).

Item Type:	Article
Uncontrolled Keywords:	Genetic algorithm Intelligent transportation system Lion optimization algorithm Quality of forwarding Vehicular ad-hoc network
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Computer Science and Information Technology > Department of Information Security
Depositing User:	Mr. Mohamad Zulkhibri Rahmad
Date Deposited:	30 Oct 2023 07:23
Last Modified:	30 Oct 2023 07:23
URI:	http://eprints.uthm.edu.my/id/eprint/10306

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