Scheduled System Maintenance:
On Wednesday, July 29th, IEEE Xplore will undergo scheduled maintenance from 7:00-9:00 AM ET (11:00-13:00 UTC). During this time there may be intermittent impact on performance. We apologize for any inconvenience.
By Topic

Coverage-aware Geocast Routing in Urban Vehicular Networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Ruobing Jiang ; Dept. of Comput. Sci. & Eng., Shanghai Jiao Tong Univ., Shanghai, China ; Yanmin Zhu

Geo cast routing in vehicular ad hoc networks plays an important role as the basis of applications such as traffic information sharing, emergency alarming, and geographic advertisement. It is quite challenging, however, to geo cast packets through multi-hop relay vehicles because of the highly dynamic network topology, large scale city road system and fast moving vehicles. Our idea is to measure vehicles' coverage capability and forward packets to those vehicles with higher probability to successfully deliver the packets. The idea is rooted in the widely accepted concept that vehicular trajectories improve packet routing and the fact that vehicular trajectories are nowadays available through widely used navigation system. To accomplish the idea, the difficulty is to measure the coverage capability of a vehicle over a specific region with only partially available vehicular trajectories without accurate timing information. We propose a novel coverage graph to maintain collected trajectories of all the encountered vehicles and their most update timing information so that the extended coverage capability of each vehicle can be estimated. The coverage graph is constructed in a distributed way based on locally shared information and the packet forwarding decisions can be adaptively made to meet different routing objectives.

Published in:

Parallel and Distributed Processing Symposium Workshops & PhD Forum (IPDPSW), 2012 IEEE 26th International

Date of Conference:

21-25 May 2012