Al-Hamid, Duaa ZuhairKaregar, Pejman AChong, Peter Han Joo2025-05-162025-05-162024-03-149798350382617http://hdl.handle.net/10292/19212With unprecedented advances in cutting-edge technologies such as Internet of Things (IoT), network virtualization, digital twin, etc., various applications such as vehicular networks (VN) need to be modelled and evaluated using suitable tools. Given the dynamic nature of VN, there is a need for a virtual flexible model that can be tested prior to implementation to avoid real-time network disruptions. It also offers network maintenance without requiring major modifications to the model in real-life execution. Therefore, software-defined networking (SDN) is one of the approaches that can provide flexibility to such applications as well as other applications such as clustering for trap monitoring using UAV. Applying this advanced technology to vehicular networks can involve significant costs and complex tools. Therefore, utilizing tools such as the Contiki-Cooja network simulator allows for trailing network scenarios and testing performance virtually to obtain the best network topology that can be applied to the physical network. The aim of the paper is to offer the modelling and implementation tools that can be employed towards concept development and testing. It provides insight into the ability of various accessible tools, including software and hardware, to investigate the concept of flexible vehicular network grouping and network re-orchestration.© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.4605 Data Management and Data Science4606 Distributed Computing and Systems Software46 Information and Computing SciencesConference ContributionOpenAccess10.1109/apcc60132.2023.10460734