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

Sami Abduljabbar Rashid (Al-Maarif University College)
Mustafa Maad Hamdi (Universiti Tun Hussein Onn Malaysia)
Lukman Audah (Imam Ja'afar Al-Sadiq University)
Mohammed Ahmed Jubair (Imam Ja'afar Al-Sadiq University)
Mustafa Hamid Hassan (Imam Ja'afar Al-Sadiq University)
Mohammed Salah Abood (Beijing Institute of Technology)
Salama A. Mostafa (Universiti Tun Hussein Onn Malaysia)

IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 12, No 2: June 2023

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).