INTEGRATION OF IOT WITH CLOUD, FOG, AND EDGE COMPUTING: A REVIEW
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Abstract
Purpose of review. The paper provides an in-depth exploration of the integration of Internet of Things (IoT) technologies with cloud, fog, and edge computing paradigms, examining the transformative impact on computational architectures. Approach to review. Beginning with an overview of IoT's evolution and its surge in global adoption, the paper emphasizes the increasing importance of integrating cloud, fog, and edge computing to meet the escalating demands for real-time data processing, low-latency communication, and scalable infrastructure in the IoT ecosystem. The survey meticulously dissects each computing paradigm, highlighting the unique characteristics, advantages, and challenges associated with IoT, cloud computing, edge computing, and fog computing. The discussion delves into the individual strengths and limitations of these technologies, addressing issues such as latency, bandwidth consumption, security, and data privacy. Further, the paper explores the synergies between IoT and cloud computing, recognizing cloud computing as a backend solution for processing vast data streams generated by IoT devices. Review results. Challenges related to unreliable data handling and privacy concerns are acknowledged, emphasizing the need for robust security measures and regulatory frameworks. The integration of edge computing with IoT is investigated, showcasing the symbiotic relationship where edge nodes leverage the residual computing capabilities of IoT devices to provide additional services. The challenges associated with the heterogeneity of edge computing systems are highlighted, and the paper presents research on computational offloading as a strategy to minimize latency in mobile edge computing. Fog computing's intermediary role in enhancing bandwidth, reducing latency, and providing scalability for IoT applications is thoroughly examined. Challenges related to security, authentication, and distributed denial of service in fog computing are acknowledged. The paper also explores innovative algorithms addressing resource management challenges in fog-IoT environments. Conclusions. The survey concludes with insights into the collaborative integration of cloud, fog, and edge computing to form a cohesive computational architecture for IoT. The future perspectives section anticipates the role of 6G technology in unlocking the full potential of IoT, emphasizing applications such as telemedicine, smart cities, and enhanced distance learning. Cybersecurity concerns, energy consumption, and standardization challenges are identified as key areas for future research.
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Seng, K. P., Ang, L. and Ngharamike, E. (2022), “Artificial intelligence Internet of Things: A new paradigm of distributed sensor networks”, International Journal of Distributed Sensor Networks, 18(3), 155014772110628, doi: https://doi.org/10.1177/15501477211062835
Lin, J., Yu, W., Zhang, N., Yang, X., Zhang, H. and Zhao, W. (2017), “A survey on Internet of things: architecture, enabling technologies, security and privacy, and applications”, IEEE Internet of Things Journal, vol. 4(5), pp. 1125–1142, doi: https://doi.org/10.1109/jiot.2017.2683200
De Donno, M., Tange, K. and Dragoni, N. (2019), “Foundations and evolution of modern computing paradigms: cloud, IoT, edge, and FOG”, IEEE Access, vol. 7, pp. 150.936–150.948, doi: https://doi.org/10.1109/access.2019.2947652
Alhaidari, F., Rahman, A. and Zagrouba, R. (2020), “Cloud of Things: architecture, applications and challenges”, Journal of Ambient Intelligence and Humanized Computing, vol. 14(5), pp. 5957–5975, doi: https://doi.org/10.1007/s12652-020-02448-3
Atlam, H. F., Walters, R. J. and Wills, G. (2018), “Fog Computing and the Internet of Things: a review”, Big Data and Cognitive Computing, vol. 2(2), doi: https://doi.org/10.3390/bdcc2020010
Alwakeel, A. M. (2021), “An overview of fog computing and edge computing security and privacy issues”, Sensors, vol. 21(24), 8226, doi: https://doi.org/10.3390/s21248226
Li, S., Da Xu, L. and Zhao, S. (2018), “5G Internet of Things: A survey”, Journal of Industrial Information Integration, vol. 10, pp. 1–9, doi: https://doi.org/10.1016/j.jii.2018.01.005
Weyrich, M. and Ebert, C. (2016), “Reference architectures for the Internet of things”, IEEE Software, vol. 33(1), pp. 112–116, doi: https://doi.org/10.1109/ms.2016.20
Ray, P. P. (2018), “A survey on Internet of Things architectures”, Journal of King Saud University - Computer and Information Sciences, vol. 30(3), pp. 291–319, doi: https://doi.org/10.1016/j.jksuci.2016.10.003
Pierleoni, P., Concetti, R., Belli, A. and Palma, L. (2020), “Amazon, Google and Microsoft Solutions for IoT: Architectures and a Performance comparison”, IEEE Access, vol. 8, pp. 5455–5470, doi: https://doi.org/10.1109/access.2019.2961511
Sethi, P. and Sarangi, S. R. (2017), “Internet of Things: architectures, protocols, and applications”, Journal of Electrical and Computer Engineering, pp. 1–25, doi: https://doi.org/10.1155/2017/9324035
Rghioui, A., Sendra, S., Lloret, J. and Oumnad, A. (2016), “Internet of things for measuring human activities in ambient assisted living and e-Health”, Network Protocols and Algorithms, vol. 8(3), p. 15, doi: https://doi.org/10.5296/npa.v8i3.10146
Landaluce, H., Arjona, L., Perallos, A., Falcone, F., Angulo, I. and Muralter, F. (2020), “A review of IoT sensing applications and challenges using RFID and wireless sensor networks”, Sensors, vol. 20(9), 2495, doi: https://doi.org/10.3390/s20092495
Vashi, S., Ram, J., Modi, J., Verma, S. and Prakash, C. (2017), “Internet of Things (IoT): A vision, architectural elements, and security issues”, 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), doi: https://doi.org/10.1109/i-smac.2017.8058399
Ngu, A. H. H., Gutiérrez, M., Metsis, V., Nepal, S. and Sheng, Q. Z. (2016), “IoT Middleware: A Survey on Issues and Enabling technologies”, IEEE Internet of Things Journal, vol. 1, doi: https://doi.org/10.1109/jiot.2016.2615180
Patil, S. B. and Chaudhari, S. (2016), “DOS attack prevention technique in wireless sensor networks”, Procedia Computer Science, vol. 79, pp. 715–721, doi: https://doi.org/10.1016/j.procs.2016.03.094
Conti, M., Dragoni, N. and Lesyk, V. (2016), “A survey of Man in the middle attacks”, IEEE Communications Surveys and Tutorials, vol. 18(3), pp. 2027–2051, doi: https://doi.org/10.1109/comst.2016.2548426
Ahmid, M. and Kazar, O. (2021), “A comprehensive review of the Internet of things security”, Journal of Applied Security Research, vol. 18(3), pp. 289–305, doi: https://doi.org/10.1080/19361610.2021.1962677
Farooq, M. U., Waseem, M., Khairi, A. and Mazhar, S. (2015), “A critical analysis on the security concerns of internet of things (IoT)”, International Journal of Computer Applications, vol. 111(7), pp. 1–6, doi: https://doi.org/10.5120/19547-1280
Gião, J., Nazarenko, A. A., Ferreira, F., Gonçalves, D. and Sarraipa, J. (2022), “A framework for Service-Oriented Architecture (SOA)-Based IoT application development”, Processes, vol. 10(9), 1782, doi: https://doi.org/10.3390/pr10091782
Uviase, O. and Kotonya, G. (2018), “IoT Architectural Framework: connection and integration framework for IoT systems”, arXiv (Cornell University), vol. 264, pp. 1–17, doi: https://doi.org/10.4204/eptcs.264.1
Maurya, S. and Mukherjee, K. (2019), “An Energy Efficient Architecture of IoT based on Service Oriented Architecture (SOA)”, Informatica, vol. 43(1), doi: https://doi.org/10.31449/inf.v43i1.1790
Li, S., Tryfonas, T. and Li, H. (2016), “The Internet of Things: a security point of view”, Internet Research, vol. 26(2), pp. 337–359, doi: https://doi.org/10.1108/intr-07-2014-0173
Chen, I., Guo, J. and Bao, F. (2016), “Trust Management for SOA-Based IoT and its application to service composition”, IEEE Transactions on Services Computing, vol. 9(3), pp. 482–495, doi: https://doi.org/10.1109/tsc.2014.2365797
Wang, F., Hu, L., Zhou, J. and Zhao, K. (2015), “A data processing middleware based on SOA for the Internet of things”, Journal of Sensors, pp. 1–8, doi: https://doi.org/10.1155/2015/827045
Gomathi, B., Balaji, B., Kumar, V. R., Abouhawwash, M., Aljahdali, S., Masud, M. and Kuchuk, N. (2022), “Multi-Objective optimization of energy aware virtual machine placement in cloud data center”, Intelligent Automation and Soft Computing, vol. 33(3), pp. 1771–1785, doi: https://doi.org/10.32604/iasc.2022.024052
Petrovska, I., Kuchuk, H. and Mozhaiev, M. (2022), “Features of the distribution of computing resources in cloud systems”, 2022 IEEE 3rd KhPI Week on Advanced Technology (KhPIWeek), doi: https://doi.org/10.1109/khpiweek57572.2022.9916459
Li, P., Li, J., Huang, Z., Gao, C., Chen, W. and Chen, K. (2017), “Privacy-preserving outsourced classification in cloud computing”, Cluster Computing, vol. 21(1), pp. 277–286, doi: https://doi.org/10.1007/s10586-017-0849-9
Abdel‐Basset, M., Mohamed, M. and Chang, V. (2018), “NMCDA: A framework for evaluating cloud computing services”, Future Generation Computer Systems, vol. 86, pp. 12–29, doi: https://doi.org/10.1016/j.future.2018.03.014
Wang, R., Yan, J., Wang, D., Wang, H. and Yang, Q. (2018), “Knowledge-Centric edge computing based on virtualized D2D communication systems”, IEEE Comm. Magazine, vol. 56(5), pp. 32–38, doi: https://doi.org/10.1109/mcom.2018.1700876
Khatatneh, K., Nawafleh, O. and Al-Utaibi, D. (2020), “The Emergence of Edge Computing Technology over Cloud Computing”, International Journal of P2P Network Trends and Technology, vol. 10(2), pp. 1–5, doi: https://doi.org/10.14445/22492615/ijptt-v10i2p401
Rimal, B. P., Van, D. P. and Maier, M. (2017), “Cloudlet enhanced Fiber-Wireless access networks for Mobile-Edge Computing”, IEEE Transactions on Wireless Communications, vol. 16(6), pp. 3601–3618, doi:
https://doi.org/10.1109/twc.2017.2685578
Wang, F., Xu, J., Wang, X. and Cui, S. (2018), “Joint offloading and computing optimization in wireless powered Mobile-Edge computing systems”, IEEE Transactions on Wireless Communications, vol. 17(3), pp. 1784–1797, doi: https://doi.org/10.1109/twc.2017.2785305
Qiu, T., Chi, J., Zhou, X., Ning, Z., Atiquzzaman, M. and Wu, D. (2020), “Edge Computing in Industrial Internet of Things: architecture, advances and challenges”, IEEE Communications Surveys and Tutorials, vol. 22(4), pp. 2462–2488, doi: https://doi.org/10.1109/comst.2020.3009103
Khan, W. Z., Ahmed, E., Hakak, S., Yaqoob, I. and Ahmed, A. (2019), “Edge computing: A survey”, Future Generation Computer Systems, vol 97, pp. 219–235, doi: https://doi.org/10.1016/j.future.2019.02.050
Yin, Y. and Deng, L. (2022), “A dynamic decentralized strategy of replica placement on edge computing”, International Journal of Distributed Sensor Networks, vol.18(8), 155013292211150, doi: https://doi.org/10.1177/15501329221115064
Breitbach, M., Schäfer, D., Edinger, J. and Becker, C. (2019), “Context-Aware Data and Task Placement in Edge Computing Environments”, 2019 IEEE Int. Conf. Pervasive Comput. Commun. PerCom, doi: https://doi.org/10.1109/percom.2019.8767386
Verma, M., Bhardwaj, N. and Yadav, A. K. (2016), “Real time efficient scheduling algorithm for load balancing in FOG computing environment”, International Journal of Information Technology and Computer Science, vol. 8(4), pp. 1–10, doi: https://doi.org/10.5815/ijitcs.2016.04.01
Hunko, M., Tkachov, V., Kovalenko, A. and Kuchuk, H. (2023), “Advantages of Fog Computing: A Comparative Analysis with Cloud Computing for Enhanced Edge Computing Capabilities”, 2023 IEEE 4th KhPI Week on Advanced Technology, KhPI Week 2023 - Conference Proceedings, 02-06 October 2023, Code 194480, doi: https://doi.org/10.1109/khpiweek61412.2023.10312948
Kraemer, F. A., Bråten, A. E., Tamkittikhun, N., & Palma, D. (2017), “FOG Computing in Healthcare–A Review and Discussion, IEEE Access, vol. 5, pp. 9.206–9.222, doi: https://doi.org/10.1109/access.2017.2704100
Rafique, H., Shah, M. A., Islam, S. U., Maqsood, T., Khan, S. and Maple, C. (2019), “A novel Bio-Inspired Hybrid Algorithm (NBIHA) for efficient resource management in Fog computing”, IEEE Access, vol. 7, pp. 115.760–115.773, doi: https://doi.org/10.1109/access.2019.2924958
Wang, T., Zhou, J., Chen, X., Wang, G., Liu, A. and Liu, Y. (2018), “A Three-Layer privacy preserving cloud storage scheme based on computational intelligence in FOG computing”, IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 2(1), pp. 3–12, doi: https://doi.org/10.1109/tetci.2017.2764109
Petrovska, I. and Kuchuk, H. (2023), “Adaptive resource allocation method for data processing and security in cloud environment”, Advanced Information Systems, vol. 7, is. 3, pp. 67–73, doi: https://doi.org/10.20998/2522-9052.2023.3.10
Dang, L. M., Piran, M. J., Han, D., Min, K. and Moon, H. (2019), “A survey on internet of things and cloud computing for healthcare”, Electronics, vol. 8(7), 768, doi: https://doi.org/10.3390/electronics8070768
Darwish, A., Hassanien, A. E., Elhoseny, M., Sangaiah, A. K. and Muhammad, K. (2017), “The impact of the hybrid platform of internet of things and cloud computing on healthcare systems: opportunities, challenges, and open problems”, Journal of Ambient Intelligence and Humanized Computing, vol. 10(10), pp. 4151–4166, doi: https://doi.org/10.1007/s12652-017-0659-1
Botta, A., De Donato, W., Persico, V. and Pescapè, A. (2016), “Integration of Cloud computing and Internet of Things: A survey”, Future Generation Computer Systems, vol. 56, pp. 684–700, doi: https://doi.org/10.1016/j.future.2015.09.021
Díáz, M., Martin, C. L. and Rubio, B. (2016), “State-of-the-art, challenges, and open issues in the integration of Internet of things and cloud computing”, Journal of Network and Computer Applications, vol. 67, pp. 99–117, doi: https://doi.org/10.1016/j.jnca.2016.01.010
Liu, Y., Fieldsend, J. E. and Min, G. (2017), “A framework of FOG Computing: architecture, challenges, and optimization”, IEEE Access, vol. 5, pp. 254.45–254.54, doi: https://doi.org/10.1109/access.2017.2766923
Kuchuk, N., Mozhaiev, O., Haichenko, А., Semenov, S., Kuchuk, H., Tiulieniev, S., Mozhaiev, M., Davydov, V., Brusakova, O. and Gnusov, Y. (2023), “Devising a method for balancing the load on a territorially distributed foggy environment”, Eastern-European Journal of Enterprise Technologies, vol. 1(4 (121)), pp. 48–55, doi: https://doi.org/10.15587/1729-4061.2023.274177
Chiang, M. and Zhang, T. (2016), “Fog and IoT: An Overview of Research Opportunities”, IEEE Internet of Things Journal, vol. 3(6), pp. 854–864, doi: https://doi.org/10.1109/jiot.2016.2584538
Puliafito, C., Mingozzi, E. and Anastasi, G. (2017), “Fog Computing for the Internet of Mobile Things: Issues and Challenges”, 2017 IEEE Int. Conf. Smart Comput, doi: https://doi.org/10.1109/smartcomp.2017.7947010
Khan, S., Parkinson, S. and Qin, Y. (2017), “Fog computing security: a review of current applications and security solutions”, Journal of Cloud Computing, vol. 6(1), doi: https://doi.org/10.1186/s13677-017-0090-3
Hamdan, S., Ayyash, M. and Almajali, S. (2020), “Edge-Computing Architectures for Internet of Things Applications: A survey”, Sensors, vol. 20(22), 6441, doi: https://doi.org/10.3390/s20226441
Li, Y., Qi, F., Wang, Z., Yu, X. and Shao, S. (2020), “Distributed edge Computing offloading algorithm based on deep reinforcement learning”, IEEE Access, vol. 8, pp. 85.204–85.215, doi: https://doi.org/10.1109/access.2020.2991773
Premsankar, G., Di Francesco, M. and Taleb, T. (2018), “Edge Computing for the Internet of Things: a case study”, IEEE Internet of Things Journal, vol/ 5(2), pp. 1275–1284, doi: https://doi.org/10.1109/jiot.2018.2805263
Xue, H., Huang, B., Qin, M., Zou, H. and Yang, H. (2020), “Edge Computing for Internet of Things: A Survey”, 2020 Int. Conf. Internet Things IEEE Green Comput. Commun. IEEE Cyber, Phys. Soc. Comput. IEEE Smart Data IEEE Congr. Cybermatics, IEEE, doi: https://doi.org/10.1109/ithings-greencom-cpscom-smartdata-cybermatics50389.2020.00130
Ketykó, I., Kecskes, L. J., Nemes, C. and Farkas, L. (2016), “Multi-user computation offloading as Multiple Knapsack Problem for 5G Mobile Edge Computing”, 2016 Eur. Conf. Networks Commun., IEEE, doi: https://doi.org/10.1109/eucnc.2016.7561037
Liu, J., Mao, Y., Zhang, J. and Letaief, K. B. (2016), “Delay-optimal computation task scheduling for mobile-edge computing systems”, 2016 IEEE Int. Symp. Inf. Theory, IEEE, doi: https://doi.org/10.1109/isit.2016.7541539
Rehman, M. H. U., Sun, C., Wah, T. Y., Iqbal, A. and Jayaraman, P. P. (2016), “Opportunistic Computation Offloading in Mobile Edge Cloud Computing Environments”, 2016 17th IEEE Int. Conf. Mob. Data Manag., IEEE, doi: https://doi.org/10.1109/mdm.2016.40
Wang, Y., Sheng, M., Wang, X., Wang, L. and Li, J. (2016), “Mobile-Edge computing: Partial computation offloading using dynamic voltage scaling” IEEE Transactions on Communications, 1, doi: https://doi.org/10.1109/tcomm.2016.2599530
Abdelwahab, S., Hamdaoui, B., Guizani, M. and Znati, T. (2016). Replisom: Disciplined Tiny Memory Replication for Massive IoT Devices in LTE Edge Cloud. IEEE Internet of Things Journal, 3(3), 327–338, doi: https://doi.org/10.1109/jiot.2015.2497263
Kuchuk, N., Ruban, І., Zakovorotnyi, O., Kovalenko, A., Shyshatskyi, A. and Sheviakov, I. (2023), “Traffic Modeling for the Industrial Internet of NanoThings”, 2023 IEEE 4th KhPI Week on Advanced Technology, KhPI Week 2023 - Conference Proceedings, 194480, doi: https://doi.org/10.1109/khpiweek61412.2023.10312856
Παπαγεωργιου, Α., Poormohammady, E. and Cheng, B. (2016), “Edge-Computing-Aware Deployment of Stream Processing Tasks Based on Topology-External Information: Model, Algorithms, and a Storm-Based Prototype”, 2016 IEEE Int. Congr. Big Data, doi: https://doi.org/10.1109/bigdatacongress.2016.40
Zhou, J., Leppänen, T., Harjula, E., Ylianttila, M., Ojala, T., Chen, Y., Jin, H. and Yang, L. T. (2013), “CloudThings: A common architecture for integrating the Internet of Things with Cloud Computing”, 2013 IEEE 17th Int. Conf. Comput. Support. Coop. Work Des. CSCWD 2013, doi: https://doi.org/10.1109/cscwd.2013.6581037
Suciu, G., Vulpe, A., Halunga, S., Fratu, O., Todoran, G. and Suciu, V. (2013), “Smart Cities Built on Resilient Cloud Computing and Secure Internet of Things”, 19th Int. Conf. Control Syst. Comput. Sci. CSCS 2013, doi: https://doi.org/10.1109/cscs.2013.58
Atlam, H. F., Alenezi, A., Alharthi, A., Walters, R. J. and Wills, G. (2017), “Integration of Cloud Computing with Internet of Things: Challenges and Open Issues”, 2017 IEEE Int. Conf. Internet Things, IEEE Green Comput. Commun. IEEE Cyber, Phys. Soc. Comput. IEEE Smart Data, doi: https://doi.org/10.1109/ithings-greencom-cpscom-smartdata.2017.105
Naveen, S. and Kounte, M. R. (2019), “Key Technologies and challenges in IoT Edge Computing”, 2019 Third International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), doi: https://doi.org/10.1109/i-smac47947.2019.9032541
Mouradian, C., Naboulsi, D., Yangui, S., Glitho, R., Morrow, M. and Polakos, P. (2018), “A comprehensive survey on FoG Computing: State-of-the-Art and Research challenges”, IEEE Communications Surveys and Tutorials, vol. 20(1), pp. 416–464, doi: https://doi.org/10.1109/comst.2017.2771153
Agarwal, S., Yadav, S. and Yadav, A. K. (2016), “An efficient architecture and algorithm for resource provisioning in Fog computing”, International Journal of Information Engineering and Electronic Business, vol. 8(1), pp. 48–61, doi: https://doi.org/10.5815/ijieeb.2016.01.06
Luan, T. H., Gao, L., Li, Z., Xiang, Y., Wei, G. and Sun, L. (2015), “Fog Computing: focusing on mobile users at the edge”, arXiv (Cornell University), doi: https://doi.org/10.48550/arxiv.1502.01815
Sabireen, H. and Venkataraman, N. (2021), A” Review on Fog Computing: Architecture, Fog with IoT, Algorithms and Research Challenges”, ICT Express, vol. 7(2), pp. 162–176, doi: https://doi.org/10.1016/j.icte.2021.05.004
Majid, M., Habib, S., Javed, A. R., Rizwan, M., Srivastava, G., Gadekallu, T. R. and Lin, J. C. (2022), “Applications of wireless sensor networks and Internet of Things Frameworks in the Industry Revolution 4.0: A Systematic Literature review”, Sensors, vol. 22(6), 2087, doi: https://doi.org/10.3390/s22062087
Gedeon, J., Brandherm, F., Egert, R., Grube, T. and Mühlhäuser, M. (2019), “What the fog? Edge Computing revisited: promises, applications and future challenges”, IEEE Access, 7, pp. 152.847–152.878, doi:
https://doi.org/10.1109/access.2019.2948399
Malik, U. M., Javed, M. A., Zeadally, S. and Islam, S. U. (2022). Energy-Efficient FOG Computing for 6G-Enabled Massive IoT: Recent trends and future opportunities. IEEE Internet of Things Journal, 9(16), 14572–14594, doi: https://doi.org/10.1109/jiot.2021.3068056
Imoize, A. L., Adedeji, O., Tandiya, N. and Shetty, S. (2021). 6G Enabled Smart Infrastructure for Sustainable Society: Opportunities, Challenges, and Research Roadmap. Sensors, 21(5), 1709, doi: https://doi.org/10.3390/s21051709