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

Year 2021, Issue: 32, 68 - 75, 31.12.2021

Muhammet Tay , Arafat Şentürk

https://doi.org/10.31590/ejosat.1040133

Cited By: 1

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.

Keywords

IoT, Edge Computing, Fog Computing, Cloud Computing.

Kenar, Sis ve Bulut Bilişimin IoT Açısından İncelenmesi

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.

Keywords

IoT, Kenar Bilişim, Sis Bilişim, Bulut Bilişim.

References

• IoT devices in use worldwide 2009-2020 | Statista. (2020). Retrieved September 30, 2020, from https://www.statista.com/statistics/764026/number-of-iot-devices-in-use-worldwide/
• Aazam, M., & Huh, E. N. (2015). Fog computing micro datacenter based dynamic resource estimation and pricing model for IoT. In Proceedings - International Conference on Advanced Information Networking and Applications, AINA (Vols. 2015-April, pp. 687–694). https://doi.org/10.1109/AINA.2015.254
• Aazam, M., St-Hilaire, M., Lung, C. H., & Lambadaris, I. (2016). PRE-Fog: IoT trace based probabilistic resource estimation at Fog. In 2016 13th IEEE Annual Consumer Communications and Networking Conference, CCNC 2016 (pp. 12–17). https://doi.org/10.1109/CCNC.2016.7444724
• 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
• Atzori, L., Iera, A., & Morabito, G. (2010). The Internet of Things: A survey. In Computer Networks (Vol. 54, Issue 15, pp. 2787–2805). https://doi.org/10.1016/j.comnet.2010.05.010
• Banka1, G. M. | K. M. | H. (2019). Internet of Things and data analytics: A current review. Wiley.
• Battula, S. K., Garg, S., Naha, R. K., Thulasiraman, P., & Thulasiram, R. (2019). A micro-level compensation-based cost model for resource allocation in a fog environment. In Sensors (Switzerland) (Vol. 19, Issue 13). https://doi.org/10.3390/s19132954
• Chinthas, A., Rani, D., & Ranjan, R. K. (2014). A Comparative Study of SaaS, PaaS and IaaS in Cloud Computing. In International Journal of Advanced Research in Computer Science and Software Engineering (Vol. 4, Issue 6). www.ijarcsse.com
• 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
• Gong, C., Liu, J., Zhang, Q., Chen, H., & Gong, Z. (2010). The characteristics of cloud computing. Proceedings of the International Conference on Parallel Processing Workshops, 275–279. https://doi.org/10.1109/ICPPW.2010.45
• Grossman, R. L. (2009). Cloud Computing. http://hadoop.apache.org/core
• Gupta, A., & Jha, R. K. (2015). A Survey of 5G Network: Architecture and Emerging Technologies. In IEEE Access (Vol. 3, pp. 1206–1232). https://doi.org/10.1109/ACCESS.2015.2461602
• 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.
• Sahni, Y., Cao, J., Zhang, S., & Yang, L. (2017). Edge Mesh: A New Paradigm to Enable Distributed Intelligence in Internet of Things. In IEEE Access (Vol. 5, pp. 16441–16458). https://doi.org/10.1109/ACCESS.2017.2739804
• 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).
• Three tier fog networks: Enabling IoT/5G for latency sensitive applications. In China Communications (Vol. 16, Issue 3, pp. 1–11). https://doi.org/10.12676/j.cc.2019.03.001
• Shi, W., Cao, J., Zhang, Q., Li, Y., & Xu, L. (2016a). Edge Computing: Vision and Challenges. In IEEE Internet of Things Journal (Vol. 3, Issue 5, pp. 637–646). https://doi.org/10.1109/JIOT.2016.2579198
• 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.
• Sultan, N. (2010). Cloud computing for education: A new dawn? International Journal of Information Management, 30(2), 109–116. https://doi.org/10.1016/j.ijinfomgt.2009.09.004
• Tiscornia, O. M., Hamamura, S., De Lehmann, E. S., González, E., Vaccaro, M. I., Otero, G., Cerini, C., & Waisman, H. (1999). LA Inervación Autonómica Gastro-Entero-Bilio-Pancreática: El concepto de “pista” plexual entérica. In Prensa Medica Argentina (Vol. 86, Issue 2, pp. 129–139).
• Tuysuz, M. F. (2019). Deneyim Kalitesi odaklı Akıllı İşbirlikçi Çoklu-erişimli Uç Hesaplama Çerçevesi QoE-based Smart Cooperative Multi-access Edge Computing Framework Deneyim Kalitesi odaklı Akıllı İşbirlikçi Çoklu-erişimli Uç Hesaplama QoE-based Smart Cooperative Multi-acces. 4(3), 8–18.
• Van Os, H. J. A., Mulder, I. A., Van Der Schaaf, I. C., Van Walderveen, M. A. A., Kapelle, L. J., Ferrari, M. D., Algra, A., & Wermer, M. J. H. (2015). The Internet of Things for Health Care: A Comprehensive Survey. In International Journal of Stroke (Vol. 10, p. 217).
• Vaquero, L. M., Rodero-Merino, L., Caceres, J., & Lindner, M. (2008). A Break in the Clouds: Towards a Cloud Definition. Computer Communication Networks.
• W. Wang, Q. W. and K. S. (2016). Multimedia Sensing as a Service (MSaaS): Exploring Resource Saving Potentials of at Cloud-Edge IoTs and Fogs. Internet of Things Journal, 4(7), 487–495.
• Wang, L., Jiao, L., Li, J., Gedeon, J., & Muhlhauser, M. (2019). MOERA: Mobility-Agnostic online resource allocation for edge computing (sayfa 7 de kaldım). IEEE Transactions on Mobile Computing, 18(8), 1843–1856. https://doi.org/10.1109/TMC.2018.2867520
• Xu, X., Fu, S., Cai, Q., Tian, W., Liu, W., Dou, W., Sun, X., & Liu, A. X. (2018). Dynamic Resource Allocation for Load Balancing in Fog Environment. In Wireless Communications and Mobile Computing (Vol. 2018). https://doi.org/10.1155/2018/6421607
• Y. Gu, Z. Chang, M. Pan, L. S. and Z. H. (2018). Joint Radio and Computational Resource Allocation in IoT Fog Computing. Transactions on Vehicular Technology, 67(8), 7475–7484.
• Y. Liu, M. Peng, G. Shou, Y. C. and S. C. (2020). Toward Edge Intelligence: Multiaccess Edge Computing for 5G and Internet of Things. Internet of Things Journal, 7(8), 6722–6747.
• Yang, Y., Wang, K., Zhang, G., Chen, X., Luo, X., & Zhou, M. T. (2018). MEETS: Maximal Energy Efficient Task Scheduling in Homogeneous Fog Networks. In IEEE Internet of Things Journal (Vol. 5, Issue 5, pp. 4076–4087). https://doi.org/10.1109/JIOT.2018.2846644
• Yu, W., Liang, F., He, X., Hatcher, W. G., Lu, C., Lin, J., & Yang, X. (2017). A Survey on the Edge Computing for the Internet of Things. In IEEE Access (Vol. 6, pp. 6900–6919). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ACCESS.2017.2778504
• Zanella, A., Bui, N., Castellani, A., Vangelista, L., & Zorzi, M. (2014). Internet of things for smart cities. In IEEE Internet of Things Journal (Vol. 1, Issue 1, pp. 22–32). https://doi.org/10.1109/JIOT.2014.2306328