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Green IoT Networks Using Machine Learning, Deep Learning for 5G Networks

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Paradigms of Smart and Intelligent Communication, 5G and Beyond

Part of the book series: Transactions on Computer Systems and Networks ((TCSN))

Abstract

Internet of Things (IoT) alludes to the enormous network interconnection of items frequently furnished with universal savvy utilized to offer savvy facilities to end clients. Although, one of the significant problems of IoT is the small power of IoT gadgets which are supposed to perform reliably for an extensive stretch of time irrespective to the battery substitution. Additionally, in search of universal IoT, quantity of IoT gadgets has detonated and tends to an enormous ascent in carbon impression of IoT networks. In such manner, power management of IoT and Green-IoT arose as exciting and alluring exploration points for both scholarly world and industry. We lead an extensive and a cutting-edge overview on novel power management procedures in IoT networks, in this chapter. Initially we introduce the difficulties of power absorption in Internet of Thing networks. After that, we will introduce novel and notable methods of power management for IoT that is yet emphasize the latest arrangements suggested in each method. Then, we will give a thorough overview of the latest power management methods for IoT environment. We will likewise introduce late patterns and new exploration points that may utilized for power preservation in IoT. At last, we will present some proposals on the most proficient method to utilization of the methods introduced in our overview to accomplish the IoT uses QoS necessities.

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Author information

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Shobhit Institute of Engineering and Technology, (Deemed-to-be-University), Modipuram, Meerut, UP, 250110, India

    Neha Jain

  2. School of Electrical and Computer Engineering, Haramaya Institute of Technology, Haramaya University, P.O. Box 138, Dire Dawa, Ethiopia

    Ritesh Pratap Singh

  3. Institute of Innovation in Technology and Management, Janakpuri, New Delhi, UP, 110058, India

    Harsh Arora

  4. Department of Electronics and Communication Engineering, G L Bajaj Institute of Technology and Management, Greater Noida, India

    Krishanu Kundu

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  1. Neha Jain
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  2. Ritesh Pratap Singh
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  3. Harsh Arora
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  4. Krishanu Kundu
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Corresponding author

Correspondence to Ritesh Pratap Singh .

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Editors and Affiliations

  1. G L Bajaj Institute of Technology and Management, Greater Noida, Uttar Pradesh, India

    Amrita Rai

  2. G L Bajaj Institute of Technology and Management, Greater Noida, Uttar Pradesh, India

    Dinesh Kumar Singh

  3. Electrical Electronics and Communication Engineering (EECE), Sharda University, Greater Noida, Uttar Pradesh, India

    Amit Sehgal

  4. Electrical and Electronics Engineering Department, Trakya University Faculty of Engineering, Trakya, Türkiye

    Korhan Cengiz

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Jain, N., Singh, R.P., Arora, H., Kundu, K. (2023). Green IoT Networks Using Machine Learning, Deep Learning for 5G Networks. In: Rai, A., Kumar Singh, D., Sehgal, A., Cengiz, K. (eds) Paradigms of Smart and Intelligent Communication, 5G and Beyond. Transactions on Computer Systems and Networks. Springer, Singapore. https://doi.org/10.1007/978-981-99-0109-8_2

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  • DOI: https://doi.org/10.1007/978-981-99-0109-8_2

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