Open Access iconOpen Access



Artificial Intelligence Based Clustering with Routing Protocol for Internet of Vehicles

Manar Ahmed Hamza1,*, Haya Mesfer Alshahrani2, Fahd N. Al-Wesabi3,4, Mesfer Al Duhayyim5, Anwer Mustafa Hilal1, Hany Mahgoub3

1 Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam bin Abdulaziz University, Alkharj, Saudi Arabia
2 Department of Information Systems, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Saudi Arabia
3 Department of Computer Science, King Khalid University, Muhayel Aseer, Saudi Arabia
4 Faculty of Computer and IT, Sana'a University, Sana'a, Yemen
5 Department of Natural and Applied Sciences, College of Community-Aflaj, Prince Sattam bin Abdulaziz University, Saudi Arabia

* Corresponding Author: Manar Ahmed Hamza. Email: email

Computers, Materials & Continua 2022, 70(3), 5835-5853.


With recent advances made in Internet of Vehicles (IoV) and Cloud Computing (CC), the Intelligent Transportation Systems (ITS) find it advantageous in terms of improvement in quality and interactivity of urban transportation service, mitigation of costs incurred, reduction in resource utilization, and improvement in traffic management capabilities. Many traffic-related problems in future smart cities can be sorted out with the incorporation of IoV in transportation. IoV communication enables the collection and distribution of real-time essential data regarding road network condition. In this scenario, energy-efficient and reliable intercommunication routes are essential among vehicular nodes in sustainable urban computing. With this motivation, the current research article presents a new Artificial Intelligence-based Energy Efficient Clustering with Routing (AI-EECR) Protocol for IoV in urban computing. The proposed AI-EECR protocol operates under three stages namely, network initialization, Cluster Head (CH) selection, and routing protocol. The presented AI-EECR protocol determines the CHs from vehicles with the help of Quantum Chemical Reaction Optimization (QCRO) algorithm. QCRO algorithm derives a fitness function with the help of vehicle speed, trust level, and energy level of the vehicle. In order to make appropriate routing decisions, a set of relay nodes was selected using Group Teaching Optimization Algorithm (GTOA). The performance of the presented AI-EECR model, in terms of energy efficiency, was validated against different aspects and a brief comparative analysis was conducted. The experimental outcomes established that AI-EECR model outperformed the existing methods under different measures.


Cite This Article

APA Style
Hamza, M.A., Alshahrani, H.M., Al-Wesabi, F.N., Duhayyim, M.A., Hilal, A.M. et al. (2022). Artificial intelligence based clustering with routing protocol for internet of vehicles. Computers, Materials & Continua, 70(3), 5835-5853.
Vancouver Style
Hamza MA, Alshahrani HM, Al-Wesabi FN, Duhayyim MA, Hilal AM, Mahgoub H. Artificial intelligence based clustering with routing protocol for internet of vehicles. Comput Mater Contin. 2022;70(3):5835-5853
IEEE Style
M.A. Hamza, H.M. Alshahrani, F.N. Al-Wesabi, M.A. Duhayyim, A.M. Hilal, and H. Mahgoub "Artificial Intelligence Based Clustering with Routing Protocol for Internet of Vehicles," Comput. Mater. Contin., vol. 70, no. 3, pp. 5835-5853. 2022.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 1695


  • 1345


  • 0


Share Link