Title: Vehicle-to-vehicle message transmission under VRP using SUMO and NS3 in an industrial area: a Pakistani case study

Authors: Jabar Mahmood; Michael Abebe Berwo; Zongtao Duan; Shehzad Ashraf Chaudhry

Addresses: State Key Laboratory of Blockchain and Data Security, School of Cyber Science and Technology and College of Computer Science and Technology, Zhejiang University, Hangzhou, 310007, China ' Hangzhou High-Tech Zone (Binjiang), Institute of Blockchain and Data Security, Hangzhou, 310053, China ' School of Information and Engineering, Chang'an University, Xi'an, 710064, China ' Department of Computer Science and Information Technology, College of Engineering, Abu Dhabi University, Abu Dhabi, UAE; Faculty of Engineering and Architecture, Department of Software Engineering, Nisantasi University, Istanbul, 34398, Türkiye

Abstract: Metropolitan cities worldwide are subject to heavy traffic, which causes inconvenience and road jams, which can also hinder business activities. Vehicular ad hoc networks (VANETs) can help avoid such inconveniences and jams by providing an automated communication architecture among vehicles roaming in the city and surrounding areas. This study examines the two- propagation loss model such as Friis and two-ray propagation loss model for inter-vehicle communication for Sialkot, which is the biggest business hub of Pakistan. We selected OpenStreetMap to import the map of Sialkot's industrial area. Then, we used SUMO to convert the map into a map.xml file, and after that, the map.xml file was converted into mobility.tcl for NS3 to perform experiments. The overall research finds that propagation loss models (PLM) affect the performance of VANETs routing protocols (VRP) during message transmission. The evaluation suggests using the Friis propagation model to gain better performance and less physical overhead.

Keywords: V2V; vehicle-to-vehicle; PLM; propagation loss model; SUMO; NS3.

DOI: 10.1504/JGBA.2025.151761

Journal for Global Business Advancement, 2025 Vol.17 No.4, pp.437 - 458

Received: 01 Apr 2025
Accepted: 09 May 2025
Published online: 18 Feb 2026 *

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