Effect of node mobility on highway mobile infostation networks
MSWIM '03 Proceedings of the 6th ACM international workshop on Modeling analysis and simulation of wireless and mobile systems
Urban multi-hop broadcast protocol for inter-vehicle communication systems
Proceedings of the 1st ACM international workshop on Vehicular ad hoc networks
TrafficView: traffic data dissemination using car-to-car communication
ACM SIGMOBILE Mobile Computing and Communications Review
V3: A Vehicle-to-Vehicle Live Video Streaming Architecture
PERCOM '05 Proceedings of the Third IEEE International Conference on Pervasive Computing and Communications
Proceedings of the 2nd ACM international workshop on Vehicular ad hoc networks
VITP: an information transfer protocol for vehicular computing
Proceedings of the 2nd ACM international workshop on Vehicular ad hoc networks
IEEE Transactions on Information Theory
A Random Linear Network Coding Approach to Multicast
IEEE Transactions on Information Theory
Fuzzy redundancy adaptation and joint source-network coding for VANET video streaming
WWIC'11 Proceedings of the 9th IFIP TC 6 international conference on Wired/wireless internet communications
Structured Peer-to-Peer Real Time Video Transmission over Vehicular Ad Hoc Networks
Mobile Networks and Applications
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Vehicular ad hoc networks (VANET) aims to enhance vehicle navigation safety by providing an early warning system: any chance of accidents is informed through the wireless communication between vehicles. For the warning system to work, it is crucial that safety messages be reliably delivered to the target vehicles in a timely manner and thus reliable and timely data dissemination service is the key building block of VANET. Data mulling technique combined with three strategies, network codeing, erasure coding and repetition coding, is proposed for the reliable and timely data dissemination service. Particularly, vehicles in the opposite direction on a highway are exploited as data mules, mobile nodes physically delivering data to destinations, to overcome intermittent network connectivity cause by sparse vehicle traffic. Using analytic models, we show that in such a highway data mulling scenario the network coding based strategy outperforms erasure coding and repetition based strategies.