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Software Defined Network Based VANET

Author

Listed:
  • Glena Aziz Qadir

    (Information System Engineering, Erbil Polytechnic University, Erbil, Iraq)

  • Shavan Askar

    (Erbil Polytechnic University, Erbil, Iraq)

Abstract

As the number of cars is growing, there is also a rapid growth in the number of road side accident. Much of these incidents have occurred by an error made by a driver. New protocols and architecture are rapidly being created for intelligent transport networks by researchers all over the world. To guarantee passengers’ safety, several companies are now encouraging an ad hoc vehicular network (VANET). In another side, before practically adopting VANET technology, there are many concerns related to this field that need to be discussed. A number of attacks can occur in the event of no or weak protection, which can be affected by the performance and reliability of the process. In order to make VANET networks more successful, it implements software defined networking (SDN) technology. This technique was briefly called SDN-VANET. The SDN in VANET framework enables us to prevent from the limitations and complexities of basic VANET structures. Through handling the whole network from a single remote controller, it allows them to reduce the overall burden on the network. In this article we describe SDN-based VANET, its working, benefits, challenges and services, applications, and security attacks.

Suggested Citation

  • Glena Aziz Qadir & Shavan Askar, 2021. "Software Defined Network Based VANET," International Journal of Science and Business, IJSAB International, vol. 5(3), pages 83-91.
    • Handle: RePEc:aif:journl:v:5:y:2021:i:3:p:83-91
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    Citations

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    Cited by:

    1. Shavan Askar & Kurdistan Ali & Tarik A. Rashid, 2021. "Fog Computing Based IoT System: A Review," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 183-196.
    2. Shavan Askar & Faris Keti, 2021. "Performance Evaluation of Different SDN Controllers," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 67-80.
    3. Shavan Askar & Ibrahim Shamal Abdulkhaleq & Shahab Wahhab Kareem, 2021. "Blockchain systems: analysis, applications, & risks," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 163-173.
    4. Shavan Askar & Kosrat Dlshad Ahmed & Shahab Wahhab Kareem, 2021. "Deep learning Utilization in SDN Networks: A Review," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 174-182.
    5. Shavan Askar & Glena Aziz Qadir & Tarik A. Rashid, 2021. "SDN Based 5G VANET: A Review," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 131-147.
    6. Shavan Askar & Baydaa Hassan Husain & Tarik A. Rashid, 2021. "SDN Based Fog Computing: A Review," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 117-130.
    7. Shavan Askar & Zhwan Mohammed Khalid & Tarik A. Rashid, 2021. "Blockchain For Securing IoT Devices: A Review," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 209-224.
    8. Ibrahim Shamal Abdulkhaleq & Shavan Askar, 2021. "Evaluating the Impact of Network Latency on the Safety of Blockchain Transactions," International Journal of Science and Business, IJSAB International, vol. 5(3), pages 71-82.
    9. Chnar Mustaf Mohammed & Shavan Askar, 2021. "Machine Learning for IoT HealthCare Applications: A Review," International Journal of Science and Business, IJSAB International, vol. 5(3), pages 42-51.
    10. Baydaa Hassan Husain & Shavan Askar, 2021. "Survey on Edge Computing Security," International Journal of Science and Business, IJSAB International, vol. 5(3), pages 52-60.
    11. Shavan Askar & Zhala Jameel Hamad & Shahab Wahhab Kareem, 2021. "Deep Learning and Fog Computing: A Review," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 197-208.
    12. Zhala Jameel Hamad & Shavan Askar, 2021. "Machine Learning Powered IoT for Smart Applications," International Journal of Science and Business, IJSAB International, vol. 5(3), pages 92-100.
    13. Shavan Askar & Chnar Mustaf Mohammed & Shahab Wahhab Kareem, 2021. "Deep Learning in IoT systems: A Review," International Journal of Science and Business, IJSAB International, vol. 5(6), pages 131-147.

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