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Study of Edge, Fog, and Cloud Computing in Terms of IoT

Year 2021, Issue: 32, 68 - 75, 31.12.2021
https://doi.org/10.31590/ejosat.1040133

Abstract

Major developments in the field of the Internet of Things (IoT) and the increase in the number of objects/devices connected to the Internet continue rapidly. With this increase, the importance of concepts such as data analysis, storage, and interpretation is increasing. This increase also raises some problems that need to be solved. Software and hardware studies are needed for the next-generation cellular network technology (5G), which is thought to be a solution to speed, bandwidth, and latency, to achieve the expected improvement. Edge, Fog and Cloud Computing (EFC) technologies are very important to respond to the needs of the new generation technology and to analyze the data emerging with the increasing IoT devices and meet the end-user needs. Having a developing and growing network structure, IoT requires reconsideration of current needs day by day. In parallel with this growth, many researchers are working in this area to overcome the problems. According to the literature study, it has been seen that the use of distributed network structure and EFC technologies rather than centralized network structure is a solution for the delay, energy-saving, and bandwidth. In this study, the latest innovations were discussed by referring to the concepts of EFC and the solutions they have provided in the field of IoT. In addition, the ongoing problems were mentioned and the results.

References

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  • Mostafa Ghobaei-Arani, Alireza Souri, A. A. R. (2019). Resource Management Approaches in Fog Computing: a Comprehensive Review Mostafa. Grid Computing.
  • Mostafa, N. (2020). Resource Selection Service Based on Neural Network in Fog Environment. Technology and Engineering Systems Journal, 408–417.
  • Nguyen Cong Luong, Yutao Jiao, Ping Wang, Dusit Niyato, Dong In Kim, and Z. H., & To. (2020). A Machine-Learning-Based Auction for Resource Trading in Fog Computing. Communications Magazine, 58(3), 82–88.
  • O’Dea, S. (2020). IoT devices in use worldwide 2009-2020. Number of IoT Devices in Use Worldwide from 2009 to 2020. https://www.statista.com/statistics/764026/number-of-iot-devices-in-use-worldwide/
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  • POOYAN HABIBI 1, (Student Member, IEEE), M. F., SEPEHR KAZEMIAN2, S. K. 2, & AND ALBERTO LEON-GARCIA 1, (Life Fellow, I. (2020). Fog Computing: A Comprehensive Architectural Survey. IEEE Access, 69105–69133.
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Kenar, Sis ve Bulut Bilişimin IoT Açısından İncelenmesi

Year 2021, Issue: 32, 68 - 75, 31.12.2021
https://doi.org/10.31590/ejosat.1040133

Abstract

Nesnelerin İnterneti (IoT) alanında yaşanan büyük gelişmeler ve internete bağlı nesne/cihaz sayısında artış hızla devam etmektedir. Bu artışla birlikte verinin analiz edilmesi, depolanması ve anlamlandırılması gibi kavramların önemi gitgide artırmaktadır. Bu artış aynı zamanda çözülmesi gereken bazı problemleri de ortaya çıkarmaktadır. Bu problemlerden hız, bant genişliği ve gecikmeye çözüm olması düşünülen yeni nesil hücresel ağ teknolojisinin (5G) beklenen iyileştirmeyi sağlayabilmesi için yazılım ve donanım çalışmalarına ihtiyaç duyulmaktadır. Yeni nesil teknolojinin ihtiyaçlarına cevap verebilme ve artan IoT cihazları ile ortaya çıkan verinin analizi ve son kullanıcı gereksinimlerinin karşılanması için Sis, Kenar ve Bulut Bilişim (KSB) teknolojileri oldukça önemlidir. Gelişen ve büyüyen bir ağ yapısına sahip olan IoT her geçen gün mevcut ihtiyaçların yeniden ele alınmasını gerektirmektedir. Bu büyümeye paralel olarak problemlerin üstesinden gelmek için birçok araştırmacı bu alanda çalışmaktadır. Yapılan literatür çalışmasına göre, merkezileştirilmiş ağ yapısından çok, dağıtılmış ağ yapısı ve KSB teknolojisinin kullanılması gecikme, enerji tasarrufu, bant genişliği için çözüm olduğu görülmüştür. Bu çalışmada KSB kavramları ile IoT alanında sağlamış oldukları çözümlere değinilerek son yenilikler ele alındı. Ayrıca hala devam eden problemlerden bahsedilerek KSB teknolojileri IoT ile karşılaştırmalı olarak analiz edilerek elde edilen sonuçlar dile getirildi.

References

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  • Alessio Botta, Walter de Donato, Valerio Persico, A. P. (2015). Integration of Cloud Computing and Internet of Things: a Survey Alessio. Future Generation Computer Systems.
  • Alsaffar, A. A., Pham, H. P., Hong, C. S., Huh, E. N., & Aazam, M. (2016). An Architecture of IoT Service Delegation and Resource Allocation Based on Collaboration between Fog and Cloud Computing. In Mobile Information Systems (Vol. 2016). https://doi.org/10.1155/2016/6123234
  • Andrews, J. G., Buzzi, S., Choi, W., Hanly, S. v., Lozano, A., Soong, A. C. K., & Zhang, J. C. (2014). What will 5G be? In IEEE Journal on Selected Areas in Communications (Vol. 32, Issue 6, pp. 1065–1082). https://doi.org/10.1109/JSAC.2014.2328098
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  • Banka1, G. M. | K. M. | H. (2019). Internet of Things and data analytics: A current review. Wiley.
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  • De Donno, M., Tange, K., & Dragoni, N. (2019). Foundations and Evolution of Modern Computing Paradigms: Cloud, IoT, Edge, and Fog. IEEE Access, 7, 150936–150948. https://doi.org/10.1109/ACCESS.2019.2947652
  • El-Sayed, H., Sankar, S., Prasad, M., Puthal, D., Gupta, A., Mohanty, M., & Lin, C. T. (2017). Edge of Things: The Big Picture on the Integration of Edge, IoT and the Cloud in a Distributed Computing Environment. IEEE Access, 6, 1706–1717. https://doi.org/10.1109/ACCESS.2017.2780087
  • F. Chiti, R. F. and B. P. (2018). A Matching Theory Framework for Tasks Offloading in Fog Computing for IoT Systems. Internet of Things Journal, 5(6), 5089–5096.
  • Gazori, P., Rahbari, D., & Nickray, M. (2020). Saving time and cost on the scheduling of fog-based IoT applications using deep reinforcement learning approach. In Future Generation Computer Systems (Vol. 110, pp. 1098–1115). https://doi.org/10.1016/j.future.2019.09.060
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  • Hamid Reza Arkian,Abolfazl Diyanat, A. P. (2017). MIST: Fog-based Data Analytics Scheme with Cost-Efficient Resource Provisioning for IoT Crowdsensing Applications. Journal of Network and Computer Applications, 82, 152–165.
  • Hayes, B. (2008). Cloud Computing. Communications of the ACM, 51(7), 9–11. https://doi.org/10.1145/1364782.1364786
  • Hesham El-Sayed, Sharmi Sankar, Mukesh Prasad, Deepak Puthal, Akshansh Gupta, M. M. (2018). Edge of Things: The Big Picture on the
  • Integration of Edge, IoT and the Cloud in a Distributed Computing Environment. IEEE Access, 6, 1706–1717.
  • High, R. (2019). IBM Edge Computing. In Ibm.
  • Huang, H., Zhu, J., & Zhang, L. (2014). Internet of Things (IoT): A vision, architectural elements, and future directions. In IET Conference Publications (Vol. 2014, Issue CP639, pp. 175–179). https://doi.org/10.1049/cp.2014.0680
  • Khurpade, J. M. (2018). A SURVEY ON IOT AND 5G NETWORK. 2018 International Conference on Smart City and Emerging Technology (ICSCET), 1–3.
  • Knorr, E., & Gruman, G. (2011). What Cloud Computing Really Means. www.infoworld.com
  • M. Chen, Y. Miao, H. Gharavi, L. H. and I. H. (2020). Intelligent Traffic Adaptive Resource Allocation for Edge Computing-based 5G Networks. Transactions on Cognitive Communications and Networking, 6(2), 499–508.
  • Marjanovic, M., Antonic, A., & Zarko, I. P. (2018). Edge computing architecture for mobile crowdsensing. IEEE Access, 6, 10662–10674. https://doi.org/10.1109/ACCESS.2018.2799707
  • McClellan, M., Cervelló-Pastor, C., & Sallent, S. (2020). Deep learning at the mobile edge: Opportunities for 5G networks. In Applied Sciences (Switzerland) (Vol. 10, Issue 14). https://doi.org/10.3390/app10144735
  • Mell, P., & Grance, T. (2011). The NIST Definition of Cloud Computing Recommendations of the National Institute of Standards and Technology.
  • Microsoft. (2021). Microsoft Azure. Retrieved September 16, 2021, from https://azure.microsoft.com/en-us/overview/what-is-saas/
  • Mostafa Ghobaei-Arani, Alireza Souri, A. A. R. (2019). Resource Management Approaches in Fog Computing: a Comprehensive Review Mostafa. Grid Computing.
  • Mostafa, N. (2020). Resource Selection Service Based on Neural Network in Fog Environment. Technology and Engineering Systems Journal, 408–417.
  • Nguyen Cong Luong, Yutao Jiao, Ping Wang, Dusit Niyato, Dong In Kim, and Z. H., & To. (2020). A Machine-Learning-Based Auction for Resource Trading in Fog Computing. Communications Magazine, 58(3), 82–88.
  • O’Dea, S. (2020). IoT devices in use worldwide 2009-2020. Number of IoT Devices in Use Worldwide from 2009 to 2020. https://www.statista.com/statistics/764026/number-of-iot-devices-in-use-worldwide/
  • Okay, F. Y. (2019). NESNELERİN İNTERNETİNDE SİS HESAPLAMA TABANLI VERİ KÜMELEME VE YÖNLENDİRME MODELLERİ.
  • POOYAN HABIBI 1, (Student Member, IEEE), M. F., SEPEHR KAZEMIAN2, S. K. 2, & AND ALBERTO LEON-GARCIA 1, (Life Fellow, I. (2020). Fog Computing: A Comprehensive Architectural Survey. IEEE Access, 69105–69133.
  • Qi, Q., & Tao, F. (2019). A Smart Manufacturing Service System Based on Edge Computing , Fog Computing , and Cloud Computing. IEEE Access, 7, 86769–86777. https://doi.org/10.1109/ACCESS.2019.2923610
  • S. F. Abedin, M. G. R. Alam, S. M. A. Kazmi, N. H. Tran, D. N. and C. S. H. (2019). Resource Allocation for Ultra-reliable and Enhanced Mobile Broadband IoT Applications in Fog Network. Transactions on Communications, 67(1), 489–502.
  • S. S. Gill, P. Garraghan, R. bUYYA. (2019). ROUTER: Fog enabled cloud based intelligent resource management approach for smart home IoT devices. The Journal of Systems and Software, 154, 125–138 Contents.
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  • Shah-Mansouri, H., & Wong, V. W. S. (2018). Hierarchical fog-cloud computing for IoT systems: A computation offloading game. In IEEE Internet of Things Journal (Vol. 5, Issue 4, pp. 3246–3257). https://doi.org/10.1109/JIOT.2018.2838022
  • Shahzadi1, R., & , Ambreen Niaz1 , Mudassar Ali1, *, Muhammad Naeem2 , Joel J.P.C. Rodrigues3, 4, 5, 6 , Farhan Qamar1, S. M. A. (2019).
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  • Shi, W., Cao, J., Zhang, Q., Li, Y., & Xu, L. (2016b). Edge Computing: Vision and Challenges. IEEE Internet of Things Journal, 3(5), 637–646. https://doi.org/10.1109/JIOT.2016.2579198
  • Stankovic, J. A. (2014). Research Directions for the Internet of Thing. Internet of Things Journal, 1(1), 3–9.
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There are 59 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

Muhammet Tay 0000-0001-5569-7886

Arafat Şentürk 0000-0002-9005-3565

Publication Date December 31, 2021
Published in Issue Year 2021 Issue: 32

Cite

APA Tay, M., & Şentürk, A. (2021). Kenar, Sis ve Bulut Bilişimin IoT Açısından İncelenmesi. Avrupa Bilim Ve Teknoloji Dergisi(32), 68-75. https://doi.org/10.31590/ejosat.1040133