Managing Congestion in Vehicular Networks Using Tabu Search

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

Abstract

© 2018, Springer Nature Switzerland AG. 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.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: EANN 2018
• Start Date: Sep 3, 2018
• End Date: Sep 5, 2018
• Acceptance Date: Jul 27, 2018
• Online Publication Date: Jul 27, 2018
• Publication Date: Jul 27, 2018
• Deposit Date: Aug 28, 2018
• Publicly Available Date: Jul 28, 2019
• 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
• DOI: https://doi.org/10.1007/978-3-319-98204-5_10
• Keywords: congestion control, tabu search, dynamic message scheduling, priorities assignment messages, VANETs highways and urban environment
• Public URL: https://uwe-repository.worktribe.com/output/861754
• Publisher URL: https://doi.org/10.1007/978-3-319-98204-5_10
• Additional Information: Additional Information : This is the accepted version of the paper. The final published version can be viewed online at https://doi.org/10.1007/978-3-319-98204-5_10; Title of Conference or Conference Proceedings : Engineering Applications of Neural Networks EANN 2018
• Contract Date: Sep 21, 2018