Improving Latency and Reliability for Vehicle System Under Fog Computing Networks

  • Mao-Lun ChiangEmail author
  • Yu-an Lin
  • Hui-Ching Hsieh
  • Weng-Chung Tsai
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 109)


In order to increase the level of convenience, people drive the car instead of walking. This case made the city’s traffic flow larger than before, and the probability of traffic accidents increase as the same time. Because of the improving in the number of traffic accidents and the dissatisfaction of road users in the vehicle network. To improve this phenomenon, the Vehicular Ad Hoc Networks (VANET) technology has been proposed. The main concept of VANET is to build an on-board sensor network, and then exchange information among the vehicles for obtaining the traffic information. In the process of information transmission, the storage and processing requirement will increase relatively. Furthermore, the latency for transmitting data between the terminal device and the data center is still an important problem that needs to be improved. In a real situation, the sensing devices under the VANET may be faulty, and these faulty devices may disturb the correctness and consistence of the overall VANET system. In order to reduce the latency and to achieve the correctness and consistency for the vehicular network system, an agreement based method for ensuring the correctness and consistency of the vehicular information system under the fog computing network has been proposed in this paper. Under the proposed three layers architecture of fog computing network, users can get the real-time traffic information of the local area with low latency and get the related information about the remote traffic condition in advanced.


Consensus Fog computing Cloud computing Agreement 


  1. 1.
    Wang, S.-C., Tseng, S.-C., Wang, S.-S., Yan, K.-Q.: Reaching safety vehicular ad hoc network of IoT. In: 17th International Telecommunications Network Strategy and Planning Symposium (Networks), pp. 150–157, November 2015Google Scholar
  2. 2.
    Laza, S.-A., Stefan, C.-E.: Future vehicular networks: what control technologies? In: 2016 International Conference on Communications (COMM), pp. 337–340 (2016)Google Scholar
  3. 3.
    Tejas, D.P., Pancholi, C., Gupta, A.: Disseminating large data in vehicular ad hoc networks. In: 2017 26th International Conference on Computer Communication and Networks (ICCCN), pp. 1–6 (2017)Google Scholar
  4. 4.
    Sookhak, M., Yu, F.R., He, Y., Talebian, H., Safa, N.S., Zhao, N., Khan, M.K., Kumar, N.: Fog vehicular computing: augmentation of fog computing using vehicular cloud computing. IEEE Veh. Technol. Mag. 12(3), 55–64 (2017)CrossRefGoogle Scholar
  5. 5.
    Namasudra, S., Roy, P., Balusamy, B.: Cloud computing: fundamentals and research issues. In: 2017 Second International Conference on Recent Trends and Challenges in Computational Models (ICRTCCM), pp. 7–12 (2017)Google Scholar
  6. 6.
    Olariu, S., Eltoweissy, M., Younis, M.: Towards autonomous vehicular clouds. ICST Trans. Mobile Commun. Appl. 11(7–9), 1–11 (2011)CrossRefGoogle Scholar
  7. 7.
    Olariu, S., Hristov, T., Yan, G.: The next paradigm shift: from vehicular networks to vehicular clouds. In: Developments in Mobile Ad Hoc Networking: The Cutting Edge Directions. Wiley, New York (2012)Google Scholar
  8. 8.
    Baby, D. et al.: VCR: vehicular cloud for road side scenarios. In: Advances in Computing and Information Technology, pp. 541–542 (2013)CrossRefGoogle Scholar
  9. 9.
    Dolui, K., Datta, S.K.: Comparison of edge computing implementations: fog computing, cloudlet and mobile edge computing. In: Global Internet of Things Summit (GIoTS), pp. 1–6 (2017)Google Scholar
  10. 10.
    Wang, S.S., Wang, S.C.: The consensus problem with dual failure nodes in a cloud computing environment. Inf. Sci. 279, 213–228 (2014)CrossRefGoogle Scholar
  11. 11.
    Hsieh, Y.L., Wang, K.: Dynamic overlay multicast for live multimedia streaming in urban VANETs. Comput. Netw. 56, 3609–3628 (2012)CrossRefGoogle Scholar
  12. 12.
    Khakimov, A., Muthanna, A., Muthanna, M.S.A.: Study of fog computing structure. In: IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus), pp. 51–54 (2018)Google Scholar
  13. 13.
    Whaiduzzaman, M., Sookhak, M., Gani, A., Buyya, R.: A survey on vehicular cloud computing. J. Netw. Comput. Appl. 40, 325–344 (2014)CrossRefGoogle Scholar
  14. 14.
    Mukherjee, M., Shu, L., Wang, D.: Survey of fog computing: fundamental, network applications, and research challenges. In: IEEE Communications Surveys & Tutorials (2018). Early accessGoogle Scholar
  15. 15.
    Bai, F., Krishnan, H.: Reliability analysis of DSRC wireless communication for vehicle safety applications. In: Intelligent Transportation Systems Conference, ITSC 2006. IEEE, Toronto (2006)Google Scholar
  16. 16.
    Moharrum, M., Al-Daraiseh, A.: Toward secure vehicular ad-hoc networks: a survey. IETE Tech. Rev. (Medknow Publications & Media Pvt. Ltd.), 29(1), 80–89 (2012)CrossRefGoogle Scholar
  17. 17.
    Zeadally, S., Hunt, R., Chen, Y.-S., Irwin, A., Hassan, A.: Vehicular ad hoc networks (VANETS): status, results, and challenges. Telecommun. Syst. 50(4), 217–241 (2012)CrossRefGoogle Scholar
  18. 18.
    Lamport, L., Shostak, R., Pease, M.: The Byzantine generals problem. ACM Trans. Program. Lang. Syst. 4(3), 382–401 (1982)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Mao-Lun Chiang
    • 1
    Email author
  • Yu-an Lin
    • 1
  • Hui-Ching Hsieh
    • 2
  • Weng-Chung Tsai
    • 1
  1. 1.Department of Information and Communication EngineeringChaoyang University of TechnologyTaichungTaiwan
  2. 2.Department of Information CommunicationHsing Wu UniversityNew Taipei CityTaiwan

Personalised recommendations