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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Mohammed Ahmed Jubair
Imam Ja'afar Al-Sadiq University
Computer Science & IT Engineering

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A collaborated genetic with lion optimization algorithms for improving the quality of forwarding in a vehicular ad-hoc network Sami Abduljabbar Rashid; Mustafa Maad Hamdi; Lukman Audah; Mohammed Ahmed Jubair; Mustafa Hamid Hassan; Mohammed Salah Abood; Salama A. Mostafa
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 12, No 2: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 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).
Co-Authors Lukman Audah Mohammed Salah Abood Mustafa Hamid Hassan Mustafa Maad Hamdi Salama A. Mostafa Sami Abduljabbar Rashid