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Fog Computing Based IoT System: A Review

Author

Listed:
  • Shavan Askar

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

  • Kurdistan Ali

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

  • Tarik A. Rashid

    (Professor, Computer Science and Engineering, University of Kurdistan Hawler, Erbil, Iraq.)

Abstract

Due to the rapid accelerated development of IoT technologies, the traditional generation cloud computing model is faced with a range of problems, including high latency, low bandwidth, and network problems. Fog computing is a new promising feature that enables legitimate cloud application services will be provided close to something like the physical IoT device at the edge devices rather than in the cloud. It's a layer that lies between the cloud and the Iot. computers that enables unified internet-based computing. How about sending IoT information to the cloud, the fog processes and stores it remotely at IoT computers. The fog in comparison to the cloud, offers resources that are more sensitive and of higher quality. As a result, fog computing could be the best option for enabling the IoT to deliver effective and reliable services to a huge number of IoT clients. After that, we'll go over some of the literature and outline the findings.

Suggested Citation

  • 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.
    • Handle: RePEc:aif:journl:v:5:y:2021:i:6:p:183-196
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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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Cheng Wang & Haiyang Huang & Jianwei Chen & Wei Wei & Tian Wang, 2020. "An online and real-time adaptive operational modal parameter identification method based on fog computing in Internet of Things," International Journal of Distributed Sensor Networks, , vol. 16(2), pages 15501477209, February.
    9. 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.
    Full references (including those not matched with items on IDEAS)

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