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Managing congestion in vehicular networks using tabu search

Ishaq, Muhammad; Malik, Mazhar Hussain; Aydin, Mehmet Emin


Muhammad Ishaq

Mazhar Hussain Malik

Mehmet Aydin
Senior Lecturer in Networks and Mobile Computing


E. Pimenidis

C. Jayne


In this era of communication, exponentially growing networks bring a lot of challenges to address for smoother network functionalities. Among them is efficiency in handling packet traffic to avoid and control congestion. A particular case is applicable to Vehicular Ad-hoc Networks, which are known with unbalanced resource utilisation, communication overheads, high transmission delay and least transmission capacity. This paper aims to minimise the delay and jitter for enhancing the Quality of Service (QoS) in Vehicular Adhoc Networks (VANET) using tabu search algorithm with multi-channel allocation capability. We proposed a scheme that prioritises each message considering the basis of message type or its substances, such as crisis, reference point, and administration oriented etc., and uses tabu search for scheduling the transmission of queued messages in order to enhance the efficiency, security, and durability of VANET. A comprehensive simulation is conducted to validate the proposed scheme and to evaluate the performances in comparison with other state-of-the-art approaches.

Journal Article Type Article
Start Date Sep 3, 2018
Publication Date Sep 1, 2018
Journal Communications in Computer and Information Science
Print ISSN 1865-0929
Publisher Springer Verlag (Germany)
Peer Reviewed Peer Reviewed
Volume 893
Pages 118-129
Series Title Communications in Computer and Information Science
Book Title Engineering Applications of Neural Networks
ISBN 9783319982038
Institution Citation Ishaq, M., Malik, M. H., & Aydin, M. E. (2018). Managing congestion in vehicular networks using tabu search. Communications in Computer and Information Science, 893, 118-129.
Keywords congestion control, tabu search, dynamic message scheduling, priorities assignment messages, VANETs highways and urban environment
Publisher URL
Additional Information Additional Information : This is the accepted version of the paper. The final published version can be viewed online at
Title of Conference or Conference Proceedings : Engineering Applications of Neural Networks EANN 2018