Eco-Networking for IoT Designing Energy-Efficient Models to Enhance Network Performance (Dr. Divya Sharma, Dr. Bishwajeet Pandey) (z-library.sk, 1lib.sk, z-lib.sk)
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IoT
Learn to design IoT models focused on reducing energy consumption and increasing network performance. This book offers a complete approach towards construction of energy-efficient models on IoT for network optimization. It describes fundamental principles of IoT and networking to advanced energy-saving and data-rate-increasing techniques. The book provides strategies for minimizing energy consumption in IoT, allowing for highest possible reliability, scale, and performance from IoT networks. We will start with basics of network protocols, data transmission, and energy consumption in IoT followed by architecture models, including low-power designs and adaptive systems. We will discuss low-power communication protocols, efficient data processing techniques, as well as network configurations and layouts for efficient IoT performance. Using AI to adaptively manage energy use will also be discussed. The book uses on practical examples, case studies, and code samples to help you learn. On completion, you will have knowledge of designing an energy-efficient IoT, low-power network protocols, data processing methods for IoT, recent technologies for optimizing the energy consumption of an IoT use case in static and dynamic environment. You Will • Learn to implement low-power networking protocols in IoT applications • Find out how to utilize energy-efficient hardware and software for data processing • Explore advanced techniques, such as AI, for dynamic energy management • Build resilient, energy-conscious IoT networks optimized for diverse application scenarios Who Is This Book For This book is for intermediate-level readers in IoT, network engineering, and environmental tech interested in specializing in green tech and power-efficient applications.
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Eco-Networking for IoT Designing Energy-Ef f icient Models to Enhance Network Performance — Dr. Divya Sharma Dr. Bishwajeet Pandey
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Eco-Networking for IoT Designing Energy-Efficient Models to Enhance Network Performance Dr. Divya Sharma Dr. Bishwajeet Pandey
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Eco-Networking for IoT: Designing Energy-Efficient Models to Enhance Network Performance ISBN-13 (pbk): 979-8-8688-2316-9 ISBN-13 (electronic): 979-8-8688-2317-6 https://doi.org/10.1007/979-8-8688-2317-6 Copyright © 2026 by Dr. Divya Sharma and Dr. Bishwajeet Pandey This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Trademarked names, logos, and images may appear in this book. Rather than use a trademark symbol with every occurrence of a trademarked name, logo, or image we use the names, logos, and images only in an editorial fashion and to the benefit of the trademark owner, with no intention of infringement of the trademark. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Managing Director, Apress Media LLC: Welmoed Spahr Acquisitions Editor: Spandana Chatterjee Development Editor: James Markham Coordinating Editor: Gryffin Winkler Copy Editor: Kezia Endsley Cover designed by eStudioCalamar Cover image by Freepik (www.freepik.com) Distributed to the book trade worldwide by Springer Science+Business Media New York, 1 New York Plaza, New York, NY 10004. Phone 1-800-SPRINGER, fax (201) 348-4505, e-mail orders-ny@springer-sbm.com, or visit www.springeronline.com. Apress Media, LLC is a Delaware LLC and the sole member (owner) is Springer Science + Business Media Finance Inc (SSBM Finance Inc). SSBM Finance Inc is a Delaware corporation. For information on translations, please e-mail booktranslations@springernature.com; for reprint, paperback, or audio rights, please e-mail bookpermissions@springernature.com. Apress titles may be purchased in bulk for academic, corporate, or promotional use. eBook versions and licenses are also available for most titles. For more information, reference our Print and eBook Bulk Sales web page at http://www.apress.com/bulk-sales. Any source code or other supplementary material referenced by the author in this book is available to readers on GitHub (https://github.com/Apress). For more detailed information, please visit https://www.apress.com/gp/services/source-code. If disposing of this product, please recycle the paper Dr. Divya Sharma Department of Computer Application, Galgotias University, Greater Noida, Uttar Pradesh, India Dr. Bishwajeet Pandey Department of Computer Application, GL Bajaj Institute of Technology and Management, Greater Noida, Uttar Pradesh, India
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xv About the Authors Dr. Divya Sharma is an assistant professor of Computer Science & Engineering at the Galgotias University, Greater Noida, India. Dr. Sharma has several research publications in reputed Scopus-indexed journals and international conferences in areas such as IoT, artificial intelligence, machine learning, and cybersecurity. She has also contributed book chapters in emerging technologies including AI and renewable energy prediction models. With experience in teaching, software development, and mentoring, she is passionate about integrating modern technologies into education and guiding students in research and innovation. Aside from her academic duties, Dr. Sharma partners with industry professionals to translate theoretical research into practical solutions and advances IoT applications in the real world. Her publications have appeared in top journals, and she has presented her research at national and international conferences. Dr. Sharma is keen to contribute to IoT and play a part in positively impacting the future of technology.
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xvi Dr. Bishwajeet Pandey is a professor at GL Bajaj Institute of Technology and Management, India. He has been a senior member of IEEE since 2019. He holds an MTech in computer science from IIIT, Gwalior, India, and a PhD in computer science from the Gran Sasso Science Institute, Italy. He has taught at esteemed institutions such as Chitkara University, Chandigarh; Jain University, Bangalore; Astana IT University, Kazakhstan; Eurasian National University, Kazakhstan (QS World Rank 321); Walsh College, USA; and UCSI University, Malaysia (QS World Rank 265). Dr. Pandey is a prolific researcher with over 30 published books and more than 240 research papers indexed in Scopus. He has garnered over 4,800 citations. His leadership roles include serving as the research head of the school of CSE at Jain University, Bangalore, from 2021 to 2023, and as the head of the International Global Academic Partnership Committee at Birla Institute of Applied Science, Bhimtal, from 2020 to 2021. In 2023, Dr. Pandey was honored with the prestigious Professor of the Year Award at Lord's Cricket Ground by the London Organization of Skills Development. Beyond his outstanding research output, his greatest strength lies in his global academic network. He has visited 49 countries, participated in 105 international conferences, and co-authored papers with 218 professors from 93 universities across 42 nations. abouT The auThors
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xvii About the Technical Reviewer Sultana Begum is a semiconductor product management expert and AI technology enthusiast with over 12 years of experience at Intel and Accenture. She is a quantum computing enthusiast with deep understanding of quantum mechanics and physics principles of Qubits. She is the lead author of the book Competitive Semiconductor Product Management. Sultana has held critical roles in technical product marketing and hardware and software product management and gained a broad and deep-rooted expertise in the semiconductor technology industry. With deep technical expertise and a keen eye for strategic thinking, her expertise spreads widely across semiconductor design development to define and execute a competitive product strategy, with hands-on experience launching multiple software and hardware products. Sultana holds bachelor’s and master’s degrees in electronics, an MBA in product management, and a Stanford LEAD Executive Management Education from Stanford University.
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1© Dr. Divya Sharma and Dr. Bishwajeet Pandey 2026 Dr. D. Sharma and Dr. B. Pandey, Eco-Networking for IoT, https://doi.org/10.1007/979-8-8688-2317-6_1 CHAPTER 1 Introduction to IoT and Green Networking The advancement of Internet of Things (IoT) technologies has transformed how devices talk to one another and has formed interlinked environments that permeate every facet of contemporary existence, spanning areas like healthcare, connected homes, automated industries, and modern farming. Nevertheless, the burgeoning expansion of IoT devices has also raised significant concerns regarding energy consumption, environmental sustainability, and the long-term viability of the actual systems.[2] This chapter examines the intersection of IoT and green networking, highlighting the importance of networking energy-efficient design in today's connected world. It presents the idea of IoT, along with its components, architecture, and the significance of networking for inter-device communication. Green networking is a paradigm that attempts to use networking systems with the smallest environmental impact by optimizing energy consumption in network processes in order to reach this goal, thus setting the stage for a deep investigation of its paper.[1] This chapter illustrates how these domains can work together harmoniously, permitting IoT and green networking to address the urgent issues of the digital age. The chapter also reveals the core concepts and methods for creating energy-efficient IoT solutions, from novel low-power communication techniques to adaptive protocols and sustainable hardware designs. It
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2 examines available case studies and real-world applications that show how green networking principles can be practically incorporated into IoT design and implementation, offering concrete illustrations of their possible effects on different industry sectors. There is a blend of technical detail and broader context, and by the end of this chapter, you will have a sense of high-level benefits of both IoT and green networking. This journey is meaningful in and of itself, but also because it highlights the urgency of aligning these technological advances with environmental stewardship—a theme that runs through every topic in the digital transformation story. IoT is not merely a technical development but a transformative concept; it is a domain-altering system of industries, societies, and human interactions. IoT allows everyday devices to connect effortlessly to the Internet, blending the physical and digital worlds to build smart systems that serve people more effectively. Be it wearables, autonomous vehicles, or industrial automation systems, these IoT applications have emerged as a foundation for contemporary innovation, enabling unmatched comfort, proficiency, and perspectives. An unprecedented, explosive growth of IoT devices has also led to important challenges, especially related to energy consumption and environment sustainability. The globe is focusing more on environmental conservation and sustainable practices than ever, but coupled with that is the rise of the IoT. Globally, the use of IoT devices is on track to cross 29 billion by the year 2030, which has further highlighted concerns over the energy footprint of these systems. Because they are built for responsiveness, IoT devices often run around the clock, using power 24-7 to collect, send, and prepare data. To add to that, their energy demand compounds and continues to grow, emitting greenhouse gases and contributing to climate change when you consider the billions of devices around the globe. As such, energy efficiency is another top requirement for IoT development, both as a matter of cost and for global sustainability. Chapter 1 IntroduCtIon to Iot and Green networkInG
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3 The Internet is generally described as a global system of interconnected computer networks that use TCP/IP communication protocols to link devices together.[1] Many of the technologies that make up the Internet have accumulated from decades of research and development in computer networking, communication systems, and information technology. This has allowed more and more devices to be connected and to talk using a local network, creating a much more connected world. Smart devices and intelligent objects, increasingly integrated into our daily lives, have given rise to this new networking paradigm. Over the past 50 years, the Internet has evolved from a small-scale system that initially linked just two computers into a global infrastructure that now connects millions, even billions, of physical smart devices. One potential solution to the energy concern is green networking, which involves a set of technologies aimed at minimizing the environmental damage caused by communication and data networks. Green networking lessens power consumption without compromising performance—and sometimes it even enhances network performance— by adopting energy-efficient protocols, hardware, and algorithms. The integration of IoT with principles of green networking can give rise to smart and eco-friendly systems. Significant progress in energy-aware routing protocols, for instance, can reduce power consumption in IoT networks, and the latest advancements in low-power wireless communication can also prolong device life and lower overall energy consumption in the IoT ecosystem. The impact of IoT and green networking goes beyond technology, shaping all aspects of society and economy. In healthcare, IoT- enabled solutions like remote patient monitoring and telemedicine are transforming access to medical care, especially in underprivileged regions. Urban areas can optimize energy use, limit waste, and create healthier, more efficient living environments. Implementing green networking principles in such applications ensures that IoT benefits are not attained at the expense of environmental harm. See Figure 1-1. Chapter 1 IntroduCtIon to Iot and Green networkInG
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AI Reading Assistant
Whole-book reading guide from stratified index samples; jump to passages in the text
AI guide
【One-Line Pitch】
A practical guide to designing IoT networks that sip rather than gulp power, pairing protocol-level fundamentals with AI-driven energy management and real deployment case studies. Best suited to intermediate IoT and network engineers who want to build greener, longer-lasting connected systems.
【Book Arc】
- **Opening (~0%–10%)**: Sets the stakes — why IoT's energy appetite, e-waste, and carbon footprint matter — and frames green networking as both an engineering and sustainability problem, illustrated with early case studies (smart agriculture, BLE healthcare, industrial IoT, wildlife tracking).
- **Early (~10%–32%)**: Builds the conceptual foundation: energy-efficient networking principles, fog/edge offloading, energy-aware link mapping and virtual network embedding, green resource allocation, and the shift toward AI-driven routing and 6G-era sustainability.
- **Middle (~32%–48%)**: Moves into architecture and hardware — layered IoT designs (edge/fog/cloud), power-reduction techniques like clock/voltage/frequency scaling, and industrial IoT energy concerns — then surveys low-power communication protocols (Zigbee, Z-Wave, Sigfox, LoRa) and their trade-offs.
- **Late (~48% onward)**: Extends into routing requirements for low-power and lossy networks, clustering and TDMA-based data aggregation, and the application of AI/ML for adaptive, dynamic energy management.
- **Ending**: Closes with green IoT case studies spanning smart cities, agriculture, healthcare, homes, transportation, and smart grids, plus challenges, future trends, and advantages of green IoT.
【Key Takeaways】
- **Energy efficiency is a first-class design constraint, not an afterthought** (Opening): the book frames power consumption as central to IoT reliability, scalability, and sustainability, tying device lifetime directly to architecture choices.
- **Layered edge–fog–cloud architectures cut power by processing data locally** (Early): offloading computation away from the cloud reduces transmission energy; cited agriculture deployments report meaningful gains over traditional cloud-only designs.
- **Energy-aware routing and virtual network embedding are core levers** (Early): traffic consolidation, dynamic link adaptation, and green resource allocation let networks meet bandwidth and latency needs while minimizing energy overhead.
- **AI/ML enables adaptive, real-time energy optimization** (Early–Late): predictive analytics and ML-driven routing adjust to traffic, battery, and environmental conditions — especially valuable in smart cities, industrial IoT, and autonomous systems.
- **Protocol choice is a trade-off, not a default** (Middle): Zigbee, Z-Wave, Sigfox, and LoRa differ sharply in data rate, device count, range, cost, and interference resistance — the right pick depends on the application's data profile.
- **Hardware-level techniques compound with network-level ones** (Middle): clock gating, voltage/frequency scaling, and process scaling reduce per-device dissipation, which sums across every layer of the architecture.
- **Clustering and data aggregation extend network lifetime** (Late): CH selection, TDMA scheduling, and in-network compression reduce transmitted packets and collisions in low-power sensor networks.
- **Green IoT spans hardware, protocols, cloud/edge, and e-waste management** (Ending): the book treats sustainability as a full-lifecycle concern, from renewable integration to disposal.
【Reading Tips】
- **Deep-read the early chapters on energy-aware routing and resource allocation** — these are the conceptual backbone the rest of the book builds on.
- **Skim the protocol comparison sections if you already know Zigbee/LoRa**, but keep the trade-off tables handy as a design reference.
- **Treat the case studies as templates, not blueprints** — extract the design pattern (e.g., local processing, mesh + solar) rather than copying specifics.
- **Watch for the AI/ML thread across chapters** — it recurs from routing to edge inference; connecting those mentions pays off.
- **Have a target use case in mind** (agriculture, smart home, industrial) so the static-vs-dynamic environment discussion stays concrete.
【Coverage Limits】
The excerpts cover the book's framing, foundational concepts, architecture, hardware optimization, and several low-power protocols in reasonable depth, but later chapters on AI-driven dynamic management, detailed case studies, and future trends are only partially represented. Specific quantitative results and code samples are largely absent from the sampled material.
Passage locations
Excerpt 1
ecializing in green tech and power-efficient applications. Eco-Networking for IoT Designing Energy-Ef f icient Models to Enhance Network Performance — Dr. Di...
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Excerpt 2
continue to spread. Fog computing facilitates the seamless delivery of service and prevents system saturation by dynamically dividing up resources at the edg...
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Excerpt 3
sipation of any architecture is the sum total of the power dissipation of all IoT devices working on every layer of the IoT architecture. Clock gating, proce...
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Excerpt 4
ission can be either single-hop (direct communication) or multi-hop (via other CHs). • Cluster head rotation: CH duties alternate on a regular basis to keep...
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