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Enhancing data delivery in vehicular networks using dual-radio architecture

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CCF Transactions on Networking

Abstract

Vehicular ad-hoc networks (VANETs) have drawn increasing attention from both academia and industry. With the proliferation of sensor and wireless technologies, a large amount of sensory data need to be transmitted among vehicles for various intelligent transportation applications such as autonomous vehicles. The conventional WiFi-based VANETs cannot perform well due to its short communication range. To this end, we introduce a hybrid dual-radio architecture consisting of a 2.4 GHz WiFi and a 433 MHz Eagle Eye (EE) radio characterized by long-range, low-rate, and low-cost communication. Through this EE radio, a mobile node can “see” more nodes in a farther distance to improve the quality of next relay selection for packet delivery using WiFi. Collaborating between WiFi and EE radios, we propose a novel dual-radio routing protocol that significantly alleviates the delivery delay in a distributed manner. To evaluate the performance, we build a dual-radio prototype to verify its feasibility and efficiency. Furthermore, extensive simulations conducted using 4000+ taxis’ trajectories in Shanghai demonstrate that the proposed dual-radio architecture and protocol can reduce up to 50% delivery delay in VANETs.

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Acknowledgements

This work was partly supported by the State Key Development Program for Basic Research of China (973 project 2014CB340303), National Natural Science Foundation of China (Grant No. 61672349, 61672353, 61672348, 61373155).

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China

    Linghe Kong, Fan Wu, Xiaofeng Gao, Min-You Wu & Guihai Chen

  2. CCF, Shanghai, China

    Linghe Kong, Fan Wu, Xiaofeng Gao, Min-You Wu & Guihai Chen

Authors
  1. Linghe Kong
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  2. Fan Wu
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  3. Xiaofeng Gao
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  4. Min-You Wu
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  5. Guihai Chen
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Correspondence to Linghe Kong.

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Kong, L., Wu, F., Gao, X. et al. Enhancing data delivery in vehicular networks using dual-radio architecture. CCF Trans. Netw. 1, 52–64 (2019). https://doi.org/10.1007/s42045-018-0002-1

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  • DOI: https://doi.org/10.1007/s42045-018-0002-1

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