A1 Journal article (refereed)
Clustering-based re-routing framework for network traffic congestion avoidance on urban vehicular roads (2023)

Ali, M., Malik, A. W., & Rahman, A. U. (2023). Clustering-based re-routing framework for network traffic congestion avoidance on urban vehicular roads. Journal of Supercomputing, 79(18), 21144-2116. https://doi.org/10.1007/s11227-023-05455-1

JYU authors or editors

Publication details

All authors or editors: Ali, Muhammad; Malik, Asad Waqar; Rahman, Anis Ur

Journal or series: Journal of Supercomputing

ISSN: 0920-8542

eISSN: 1573-0484

Publication year: 2023

Publication date: 19/06/2023

Volume: 79

Issue number: 18

Pages range: 21144–2116

Publisher: Springer

Publication country: Netherlands

Publication language: English

DOI: https://doi.org/10.1007/s11227-023-05455-1

Research data link: https://github.com/IhabMoha/datasets-for-VANET

Publication open access: Not open

Publication channel open access: 

Abstract

With advancing vehicular technology, there are challenges related to the computing capabilities of the deployed infrastructure. In a dense vehicular network, the system performance quickly degrades due to the scarcity of computing capacity and the heavy workload on the coordinating nodes. In situations of a road accident or slow-moving traffic, many trigger messages are generated to enable situational awareness. Aforesaid events may lead to network congestion across the vehicular environment resulting in higher packet loss. Moreover, emergency messages incur increased service delays rather than getting preference for servicing. In this work, we propose a clustering-based re-routing framework for network traffic congestion avoidance on urban vehicular roads. We use queue optimization to categorize and execute tasks based on their priority level at each fog node. Moreover, threshold-based congestion detection is used to determine congested nodes, which, alongside clustering-based suitable node selection, is used for workload sharing. Furthermore, a re-routing mechanism is implemented to decrease packet loss, improving the delivery rate. The simulation results show that the proposed technique is reliable, effective, and robust in terms of packet loss, throughput, and delivery of emergency messages.

Keywords: unstructured networks; wireless data transmission; traffic; road traffic; vehicles; emergency messages; traffic control; intelligent transportation systems

Free keywords: vehicular network; congestion control; clustering; emergency messages

Contributing organizations

Ministry reporting: Yes

VIRTA submission year: 2023

JUFO rating: 1