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Deep learning Utilization in SDN Networks: A Review

Author

Listed:
  • Shavan Askar

    (Assistant Professor, CEO of Arcella Telecom, College of Engineering, Erbil Polytechnic University, Erbil, Iraq.)

  • Kosrat Dlshad Ahmed

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

  • Shahab Wahhab Kareem

    (Lecturer, Erbil Polytechnic University, Erbil, Iraq.)

Abstract

The contexts of SDN or Software Defined Network deliver increased level of programmable and functionality within the network development, network configuration and development of the dynamic management in the software protocol. SDN concept also provides centralized management and development approach for the network selection, network control and data plans. In this paper, different deep learning models and technical processes for the SDN networks have been reviewed.

Suggested Citation

  • 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.
    • Handle: RePEc:aif:journl:v:5:y:2021:i:6:p:174-182
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    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Zhwan Mohammed Khalid & Shavan Askar, 2021. "Resistant Blockchain Cryptography to Quantum Computing Attacks," International Journal of Science and Business, IJSAB International, vol. 5(3), pages 116-125.
    4. 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.
    5. Kosrat Dlshad Ahmed & Shavan Askar, 2021. "Deep Learning Models for Cyber Security in IoT Networks: A Review," International Journal of Science and Business, IJSAB International, vol. 5(3), pages 61-70.
    6. Volodymyr Mnih & Koray Kavukcuoglu & David Silver & Andrei A. Rusu & Joel Veness & Marc G. Bellemare & Alex Graves & Martin Riedmiller & Andreas K. Fidjeland & Georg Ostrovski & Stig Petersen & Charle, 2015. "Human-level control through deep reinforcement learning," Nature, Nature, vol. 518(7540), pages 529-533, February.
    7. 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.
    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. Kurdistan Ali & Shavan Askar, 2021. "Security Issues and Vulnerability of IoT Devices," International Journal of Science and Business, IJSAB International, vol. 5(3), pages 101-115.
    Full references (including those not matched with items on IDEAS)

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