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Network coding with crowdsourcing-based trajectory estimation for vehicular networks

delete2016-04-01
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Lingzhi Li *
杨哲 cover
杨哲 (Zhe Yang)
王进 (Jin Wang)
S
Shukui Zhang
DOI:10.1016/j.jnca.2016.02.001delete
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Abstract

Abstract

En 中文
It is a great challenge to transmit data in vehicular networks, where the link among nodes is very shaky because of the rapid movement of vehicles. In this paper, we propose a Network Coding with Crowdsourcing-based Trajectory Estimation (NC/CTE) method to transmit data in vehicular networks. Key points are designated beforehand in movement area. Every node estimates which of Key points the other nodes in the discovered area close to at the different times. The estimation is completed by every node in crowdsourcing method based on the pre-trajectory of GPS navigation. Network coding, recoding and reverse forwarding are used for data transmission according to the result of trajectory estimation. Simulation results show that NC/CTE is able to cut down 1/2 overhead messages of TBNC when mobile nodes have shared their GPS trajectories. It improves the reliability and scalability of vehicular networks. (C) 2016 Elsevier Ltd. All rights reserved.
Keywords:
Vehicular networks
Network coding
Crowdsourcing
Trajectory estimation
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Journal

Journal of Network and Computer Applications cover
Journal of Network and Computer Applications
IF:
8
Papers:
3.6K
Citations:
1.1W

Organization

S
soochow university - china
Scholars:
5.2W
Papers: 3.6W
Citations: 82