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Published in: Neural Computing and Applications 7/2020

25-06-2019 | Original Article

Distance and signal quality aware next hop selection routing protocol for vehicular ad hoc networks

Authors: Kashif Naseer Qureshi, Faisal Bashir, Abdul Hanan Abdullah

Published in: Neural Computing and Applications | Issue 7/2020

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Abstract

Newly emerged and integrated data communication technologies have changed the traditional processes and improve the quality of services. Wireless networks also provide efficient, low cost, fast and reliable solutions for different fields of life. Vehicular ad hoc networks are intended with various new smart features and make the inter communication systems for transportation and provide safety and comfort on the roads and establish the communication platform. However, because of unpredictable dense and sparse traffic conditions in urban areas, data communication is a challenging task for effective and reliable data links. Various topology-, location- and cluster-based protocols have been adopted to deal with high mobility of nodes and dynamic nature of network topologies. This paper presents a distance and signal quality aware routing (DSQR) protocol to deal with vehicular networks. The propose protocol initiates its forwarding decision based on Mid-Area node selection by evaluating direction and distance of neighbour nodes and also taking link quality into account and selects the best next forwarder node towards the destination node. The performance of DSQR is evaluated carrying out with vehicle speed and traffic density in realistic environment. Performance comparisons evaluation indicated the higher performance of propose protocol compared with existing protocols and reduces packet dropping and link failure issues.

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Metadata
Title
Distance and signal quality aware next hop selection routing protocol for vehicular ad hoc networks
Authors
Kashif Naseer Qureshi
Faisal Bashir
Abdul Hanan Abdullah
Publication date
25-06-2019
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 7/2020
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-019-04320-8

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