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Advance Cloud Data Analytics for 5G Enabled IoT

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Blockchain for 5G-Enabled IoT

Abstract

The mobile cellular networks such as 5G are evolving from the existing 4G networks and will continue to provide better services to the end-users. Over time, the number of Internet of Things (IoT) devices will be linked with the 5G networks to provide support for low latency and ultra-reliable communication. The main drawback is the decision process management and handling vast amounts of data associated with the IoT and 5G based systems. Hence the adoption of Cloud Computing (CC), 5G, and IoT is an important keyword for its implementation. The market interest in the IoT is increased because of the improvements in the 5G and CC technologies. The 5G can cater to present requirements like smart energy applications, etc. and many to come in the future timeline. The 5G users can be categorized into latency calculation, enhanced mobile broadband (eMBB), and critical communications for massive IoT clusters. CC will help to handle the information volumes generated by IoT, as 5G boosts the network capacity. These combinations of technologies such as CC, IoT, and 5G will be a boon to industries such as automotive and mobility, media and content, Public/smart city, healthcare, manufacturing, energy, and utility. The contribution of this chapter is the benefits the 5G enabled IoT system will get by integrating with the Cloud ecosystem. The outcome of the case study reflects the benefits of using the Cloud ecosystem for the 5G based IoT infrastructure for an effective decision-making process via intelligent communication mechanism and handling security in the IoT framework. abstract environment.

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References

  1. I. Mistry, S. Tanwar, S. Tyagi, N. Kumar, Blockchain for 5G-enabled IoT for industrial automation: A systematic review, solutions, and challenges. Mech. Syst. Signal Process. 135, 106382 (2020)

    Article  Google Scholar 

  2. V.K. Prasad, M.D. Bhavsar, Monitoring and prediction of SLA for IoT based cloud. Scalable Comput. Pract. Exp. 21(3), 349–358 (2020)

    Article  Google Scholar 

  3. M.T. Vega, C. Liaskos, S. Abadal, E. Papapetrou, A. Jain, B. Mouhouche, G. Kalem et al., Immersive interconnected virtual and augmented reality: a 5G and IoT perspective. J. Netw. Syst. Manag. 28, 1–31 (2020)

    Google Scholar 

  4. A. Kumari, S. Tanwar, S. Tyagi, N. Kumar, M.S. Obaidat, J.J.P.C. Rodrigues, Fog computing for smart grid systems in the 5G environment: challenges and solutions. IEEE Wirel. Commun. 26(3), 47–53 (2019)

    Article  Google Scholar 

  5. A. Khalil, H. Farman, B. Jan, Z. Khan, A. Koubâa, A smart energy-based source location privacy preservation (SESLPP) model for IoT-based VANETs. Trans. Emerg. Telecommun. Technol., 28, 1–14 (2020)

    Google Scholar 

  6. V.K. Prasad, M. Shah, M.D. Bhavsar, Trust management and monitoring at an IaaS level of cloud computing, in Proceedings of 3rd International Conference on Internet of Things and Connected Technologies (ICIoTCT) (2018), pp. 26–27

    Google Scholar 

  7. V.K. Prasad, M.D. Bhavsar, Exhausting autonomic techniques for meticulous consumption of resources at an IaaS layer of cloud computing, in International Conference on Future Internet Technologies and Trends (Springer, Cham, 2017), pp. 37–46

    Google Scholar 

  8. L.J. Vora, Evolution of mobile generation technology: 1G to 5G and review of upcoming wireless technology 5G. Int. J. Mod. Trends Eng. Res. 2(10), 281–290 (2015)

    Google Scholar 

  9. D. Wang, D. Chen, B. Song, N. Guizani, X. Yu, X. Du, From IoT to 5G I-IoT: the next generation IoT-based intelligent algorithms and 5G technologies. IEEE Commun. Mag. 56(10), 114–120 (2018)

    Article  Google Scholar 

  10. I. Memon, H. Fazal, R.A. Shaikh, G. Muhammad, Q.A. Arain, T.K. Khatri, Big data, cloud and 5G networks create smart and intelligent world: a survey. Univ. Sindh J. Inf. Commun. Technol. 3(4), 185–192 (2019)

    Google Scholar 

  11. V.K. Prasad, M. Bhavsar, Efficient resource monitoring and prediction techniques in an IaaS level of cloud computing: survey, in International Conference on Future Internet Technologies and Trends (Springer, Cham, 2017), pp. 47–55

    Google Scholar 

  12. M. Marjani, F. Nasaruddin, A. Gani, A. Karim, I.A.T. Hashem, A. Siddiqa, I. Yaqoob, Big IoT data analytics: architecture, opportunities, and open research challenges. IEEE Access 5, 5247–5261 (2017)

    Article  Google Scholar 

  13. J.H. Kim, A review of cyber-physical system research relevant to the emerging IT trends: industry 4.0, IoT, big data, and cloud computing. J. Ind. Integr. Manag. 2(03), 1750011 (2017)

    Google Scholar 

  14. L.D. Xu, E.L. Xu, L. Li, Industry 4.0: state of the art and future trends. Int. J. Prod. Res. 56(8), 2941–2962 (2018)

    Google Scholar 

  15. H. Ahuett-Garza, T. Kurfess, A brief discussion on the trends of habilitating technologies for industry 4.0 and smart manufacturing. Manuf. Lett. 15, 60–63 (2018)

    Google Scholar 

  16. S.K. Rao, R. Prasad, Impact of 5G technologies on industry 4.0. Wirel. Pers. Commun. 100(1), 145–159 (2018)

    Google Scholar 

  17. V.K. Prasad, M. Shah, N. Patel, M. Bhavsar, Inspection of trust based cloud using security and capacity management at an IaaS level. Procedia Comput. Sci. 132, 1280–1289 (2018)

    Article  Google Scholar 

  18. I.M.A. Jawarneh, P. Bellavista, L. Foschini, G. Martuscelli, R. Montanari, A. Palopoli, F. Bosi, QoS and performance metrics for container-based virtualization in cloud environments, in Proceedings of the 20th International Conference on Distributed Computing and Networking (2019), pp. 178–182

    Google Scholar 

  19. L. Zhang, G. Zhao, M.A. Imran, Internet of Things and sensors networks in 5G Wireless communications, in MDPI (2020)

    Google Scholar 

  20. F. Qamar, Mohammad Nour Hindia, Talib Abbas, Kaharudin Bin Dimyati, and Iraj Sadegh Amiri, Investigation of QoS performance evaluation over 5G network for indoor environment at millimeter wave bands. Int. J. Electron. Telecommun. 65(1), 95–101 (2019)

    Google Scholar 

  21. M. Pathan, J. Broberg, R. Buyya, Maximizing utility for content delivery clouds, in International Conference on Web Information Systems Engineering (Springer, Berlin, 2009), pp. 13–28

    Google Scholar 

  22. H. Mehta, V.K. Prasad, M. Bhavsar, Efficient resource scheduling in cloud computing. Int. J. Adv. Res. Comput. Sci. 8(3), 809–815 (2017)

    Google Scholar 

  23. S. Tanwar, S. Tyagi, I. Budhiraja, N. Kumar, Tactile Internet for autonomous vehicles: latency and reliability analysis. IEEE Wirel. Commun. 26(4), 66–72 (2019)

    Article  Google Scholar 

  24. A. Mewada, R. Gujaran, V.K. Prasad, V. Chudasama, A. Shah, M. Bhavsar, Establishing trust in the cloud using machine learning methods, in Proceedings of First International Conference on Computing, Communications, and Cyber-Security (IC4S 2019) (Springer, Singapore, 2020), pp. 791–805

    Google Scholar 

  25. S. Tyagi, S. Tanwar, N. Kumar, J.J.P.C. Rodrigues, Cognitive radio-based clustering for opportunistic shared spectrum access to enhance lifetime of wireless sensor network. Pervas. Mobile Comput. 22, 90–112 (2015)

    Article  Google Scholar 

  26. U. Bodkhe, D. Mehta, S. Tanwar, P. Bhattacharya, P.K. Singh, W.-C. Hong, A survey on decentralized consensus mechanisms for cyber physical systems. IEEE Access 8, 54371–54401 (2020)

    Article  Google Scholar 

  27. V.K. Prasad, M.D. Bhavsar, Monitoring IaaS cloud for healthcare systems: healthcare information management and cloud resources utilization. Int. J. E-Health Med. Commun. (IJEHMC) 11(3), 54–70 (2020)

    Google Scholar 

  28. P. O’Donovan, C. Gallagher, K. Leahy, D.T.J. O’Sullivan, A comparison of fog and cloud computing cyber-physical interfaces for Industry 4.0 real-time embedded machine learning engineering applications. Comput. Ind. 110, 12–35 (2019)

    Google Scholar 

  29. J. Du, L. Zhao, J. Feng, X. Chu, Computation offloading and resource allocation in mixed fog/cloud computing systems with min-max fairness guarantee. IEEE Trans. Commun. 66(4), 1594–1608 (2018)

    Article  Google Scholar 

  30. Z. Ning, J. Huang, X. Wang, Vehicular fog computing: enabling real-time traffic management for smart cities. IEEE Wirel. Commun. 26(1), 87–93 (2019)

    Article  Google Scholar 

  31. H.A. Khattak, H. Arshad, S. ul Islam, G. Ahmed, S. Jabbar, A.M. Sharif, S. Khalid, Utilization and load balancing in fog servers for health applications. EURASIP J. Wirel. Commun. Netw. 2019(1), 91 (2019)

    Google Scholar 

  32. N. Pontois, M. Kaneko, T.H.L. Dinh, L. Boukhatem, User pre-scheduling and beamforming with outdated CSI in 5G fog radio access networks, in 2018 IEEE Global Communications Conference (GLOBECOM) (IEEE, Piscataway, 2018), pp. 1–6

    Book  Google Scholar 

  33. R. Moreno-Vozmediano, R.S. Montero, E. Huedo, I.M. Llorente, Cross-site virtual network in cloud and fog computing. IEEE Cloud Comput. 4(2), 46–53 (2017)

    Article  Google Scholar 

  34. G. Lee, W. Saad, M. Bennis, An online optimization framework for distributed fog network formation with minimal latency. IEEE Trans. Wirel. Commun. 18(4), 2244–2258 (2019)

    Article  Google Scholar 

  35. M. Ali, N. Riaz, M.I. Ashraf, S. Qaisar, M. Naeem, Joint cloudlet selection and latency minimization in fog networks. IEEE Trans. Ind. Inf. 14(9), 4055–4063 (2018)

    Article  Google Scholar 

  36. S.Z. Tajalli, S.A.M. Tajalli, A. Kavousi-Fard, T. Niknam, M. Dabbaghjamanesh, S. Mehraeen, A secure distributed cloud-fog based framework for economic operation of microgrids, in 2019 IEEE Texas Power and Energy Conference (TPEC) (IEEE, Piscataway, 2019), pp. 1–6

    Google Scholar 

  37. E.B.C. Barros, B.G. Batista, B.T. Kuehne, M.L.M. Peixoto, Fog computing model to orchestrate the consumption and production of energy in microgrids. Sensors 19(11), 2642 (2019)

    Google Scholar 

  38. T. Wang, Y. Liang, W. Jia, M. Arif, A. Liu, M. Xie, Coupling resource management based on fog computing in smart city systems. J. Netw. Comput. Appl. 135, 11–19 (2019)

    Article  Google Scholar 

  39. Y. Dong, S. Guo, J. Liu, Y. Yang, Energy-efficient fair cooperation fog computing in mobile edge networks for smart city. IEEE Internet Things J. 6(5), 7543–7554 (2019)

    Article  Google Scholar 

  40. Y. Zhou, Q. Shen, M. Dong, K. Ota, J. Wu, Chaos-based delay-constrained green security communications for fog-enabled information-centric multimedia network, in 2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring), April (IEEE, Piscataway, 2019), pp. 1–6

    Google Scholar 

  41. J. Pereira, L. Ricardo, M. Luís, C. Senna, S. Sargento, Assessing the reliability of fog computing for smart mobility applications in VANETs. Future Gener. Comput. Syst. 94, 317–332 (2019)

    Article  Google Scholar 

  42. Y.-S. Chen, Y.-T. Tsai, A mobility management using follow-me cloud-cloudlet in fog-computing-based RANs for smart cities. Sensors 18(2), 489 (2018)

    Google Scholar 

  43. N. Moustafa, A systemic IoT-fog-cloud architecture for big-data analytics and cyber security systems: a review of fog computing (2019). Preprint. arXiv:1906.01055

    Google Scholar 

  44. A. Yassine, S. Singh, M.S. Hossain, G. Muhammad, IoT big data analytics for smart homes with fog and cloud computing. Future Gener. Comput. Syst. 91, 563–573 (2019)

    Article  Google Scholar 

  45. M. Nasir, K. Muhammad, J. Lloret, A.K. Sangaiah, M. Sajjad, Fog computing enabled cost-effective distributed summarization of surveillance videos for smart cities. J. Parallel Distrib. Comput. 126, 161–170 (2019)

    Article  Google Scholar 

  46. SmartcitiesWorld, https://www.smartcitiesworld.net/news/news/how-5g-powered-robots-are-helping-china-fight-coronavirus-5154. Last access 22 Oct 2020

  47. J. Vora, P. Italiya, S. Tanwar, S. Tyagi, N. Kumar, M.S. Obaidat, K.-F. Hsiao, Ensuring privacy and security in E-health records, in 2018 International Conference on Computer, Information and Telecommunication Systems (CITS) (IEEE, Piscataway, 2018), pp. 1–5

    Google Scholar 

  48. R. Jaiswal, A. Agarwal, R. Negi, Smart solution for reducing the COVID-19 risk using smart city technology. IET Smart Cities 2(2), 82–88 (2020)

    Article  Google Scholar 

  49. S.K. Rao, R. Prasad, Impact of 5G technologies on industry 4.0. Wirel. Pers. Commun. 100(1), 145–159 (2018)

    Google Scholar 

  50. F. Al-Turjman, Intelligence and security in big 5G-oriented IoNT: an overview. Future Gener. Comput. Syst. 102, 357–368 (2020)

    Article  Google Scholar 

  51. The Ericsson Mobility Report, https://www.ericsson.com/en/mobility-report. Last access: 22 Oct 2020

  52. J. Cao, M. Ma, H. Li, R. Ma, Y. Sun, P. Yu, L. Xiong, A survey on security aspects for 3GPP 5G networks. IEEE Commun. Surv. Tutorials 22(1), 170–195 (2019)

    Article  Google Scholar 

  53. P. Ameigeiras, J.J. Ramos-Munoz, L. Schumacher, J. Prados-Garzon, J. Navarro-Ortiz, J.M. Lopez-Soler, Link-level access cloud architecture design based on SDN for 5G networks. IEEE Netw. 29(2), 24–31 (2015)

    Article  Google Scholar 

  54. Z. Lü, Y. Lü, M. Yuan, Z. Wang, A heterogeneous large-scale parallel SCADA/DCS architecture in 5G OGCE, in 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) (IEEE, Piscataway, 2017), pp. 1–7

    Google Scholar 

  55. I. Ahmad, T. Kumar, M. Liyanage, J. Okwuibe, M. Ylianttila, A. Gurtov, 5G security: analysis of threats and solutions, in 2017 IEEE Conference on Standards for Communications and Networking (CSCN) (IEEE, Piscataway, 2017), pp. 193–199

    Google Scholar 

  56. H. Zhang, N. Liu, X. Chu, K. Long, A.-H. Aghvami, V.C.M. Leung, Network slicing based 5G and future mobile networks: mobility, resource management, and challenges. IEEE Commun. Mag. 55(8), 138–145 (2017)

    Article  Google Scholar 

  57. O. Aydin, E.A. Jorswieck, D. Aziz, A. Zappone, Energy-spectral efficiency tradeoffs in 5G multi-operator networks with heterogeneous constraints. IEEE Trans. Wirel. Commun. 16(9), 5869–5881 (2017)

    Article  Google Scholar 

  58. I.S. Udoh, G. Kotonya, Developing IoT applications: challenges and frameworks. IET Cyber-Phys. Syst. Theory Appl. 3(2), 65–72 (2018)

    Article  Google Scholar 

  59. M. Alzenad, M.Z. Shakir, H. Yanikomeroglu, M.-S. Alouini, FSO-based vertical backhaul/fronthaul framework for 5G+ wireless networks. IEEE Commun. Mag. 56(1), 218–224 (2018)

    Article  Google Scholar 

  60. I. Ahmad, T. Kumar, M. Liyanage, J. Okwuibe, M. Ylianttila, A. Gurtov, 5G security: analysis of threats and solutions, in 2017 IEEE Conference on Standards for Communications and Networking (CSCN) (IEEE, Piscataway, 2017), pp. 193–199

    Google Scholar 

  61. A. Ahad, M. Tahir, K.-L. Alvin Yau, 5G-based smart healthcare network: architecture, taxonomy, challenges and future research directions. IEEE Access 7, 100747–100762 (2019)

    Article  Google Scholar 

  62. I. Ahmad, T. Kumar, M. Liyanage, J. Okwuibe, M. Ylianttila, A. Gurtov, Overview of 5G security challenges and solutions. IEEE Commun. Stand. Mag. 2(1), 36–43 (2018)

    Article  Google Scholar 

  63. M.R. Palattella, M. Dohler, A. Grieco, G. Rizzo, J. Torsner, T. Engel, L. Ladid, Internet of things in the 5G era: enablers, architecture, and business models. IEEE J. Sel. Areas Commun. 34(3), 510–527 (2016)

    Article  Google Scholar 

  64. S. Li, Q. Ni, Y. Sun, G. Min, S. Al-Rubaye, Energy-efficient resource allocation for industrial cyber-physical IoT systems in 5G era. IEEE Trans. Ind. Inf. 14(6), 2618–2628 (2018)

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India

    Vivek Kumar Prasad, Sudeep Tanwar & Madhuri D. Bhavsar

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  1. Vivek Kumar Prasad
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Correspondence to Vivek Kumar Prasad .

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  1. Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India

    Sudeep Tanwar

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Prasad, V.K., Tanwar, S., Bhavsar, M.D. (2021). Advance Cloud Data Analytics for 5G Enabled IoT. In: Tanwar, S. (eds) Blockchain for 5G-Enabled IoT. Springer, Cham. https://doi.org/10.1007/978-3-030-67490-8_7

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  • DOI: https://doi.org/10.1007/978-3-030-67490-8_7

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