Literature Database Entry

tian2016trad


Bin Tian, K. M. Hou and Jianjin Li, "TrAD: Traffic Adaptive Data Dissemination Protocol for Both Urban and Highway VANETs," Proceedings of 30th International Conference on Advanced Information Networking and Applications (AINA 2016), Crans-Montana, Switzerland, March 2016.

Abstract

Vehicular Ad hoc Networks (VANETs) aim to improve transportation activities that include traffic safety, transport efficiency and even infotainment on the wheels, in which a great number of traffic event-driven messages are needed to disseminate in a region of interest timely. However, due to the nature of VANETs, highly dynamic mobility and frequent disconnection, data dissemination faces great challenges. Inter-Vehicle Communication (IVC) protocols are the key technology to mitigate this issue. Therefore, we propose an infrastructure-less Traffic Adaptive data Dissemination (TrAD) protocol that considers road traffic and highway, network traffic status for both and topology, urban scenarios. TrAD is flexible to fit the irregular road and maps, owns double broadcast suppression techniques. Three state-of-the-art IVC protocols have been compared with TrAD by means of realistic simulations. The performance of all protocols is quantitatively evaluated with different real city and traffic routes. Finally, TrAD gets an outstanding overall performance in terms of several metrics, even though under the worse condition of GPS drift.

Quick access

BibTeX BibTeX

Contact

Bin Tian
K. M. Hou
Jianjin Li

BibTeX reference

@inproceedings{tian2016trad,
    author = {Tian, Bin and Hou, K. M. and Li, Jianjin},
    title = {{TrAD: Traffic Adaptive Data Dissemination Protocol for Both Urban and Highway VANETs}},
    booktitle = {30th International Conference on Advanced Information Networking and Applications (AINA 2016)},
    year = {2016},
    month = {March},
    address = {Crans-Montana, Switzerland},
    publisher = {IEEE},
   }
   
   

Copyright notice

Links to final or draft versions of papers are presented here to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or distributed for commercial purposes without the explicit permission of the copyright holder.

The following applies to all papers listed above that have IEEE copyrights: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

The following applies to all papers listed above that are in submission to IEEE conference/workshop proceeedings or journals: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.

The following applies to all papers listed above that have ACM copyrights: ACM COPYRIGHT NOTICE. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Publications Dept., ACM, Inc., fax +1 (212) 869-0481, or permissions@acm.org.

The following applies to all SpringerLink papers listed above that have Springer Science+Business Media copyrights: The original publication is available at www.springerlink.com.

This page was automatically generated using BibDB and bib2web.