Green Machine Learning Protocols For Future Communication Networks
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| Author | : Saim Ghafoor |
| Publisher | : CRC Press |
| Total Pages | : 249 |
| Release | : 2023-10-25 |
| Genre | : Computers |
| ISBN | : 1000968936 |
Machine learning has shown tremendous benefits in solving complex network problems and providing situation and parameter prediction. However, heavy resources are required to process and analyze the data, which can be done either offline or using edge computing but also requires heavy transmission resources to provide a timely response. The need here is to provide lightweight machine learning protocols that can process and analyze the data at run time and provide a timely and efficient response. These algorithms have grown in terms of computation and memory requirements due to the availability of large data sets. These models/algorithms also require high levels of resources such as computing, memory, communication, and storage. The focus so far was on producing highly accurate models for these communication networks without considering the energy consumption of these machine learning algorithms. For future scalable and sustainable network applications, efforts are required toward designing new machine learning protocols and modifying the existing ones, which consume less energy, i.e., green machine learning protocols. In other words, novel and lightweight green machine learning algorithms/protocols are required to reduce energy consumption which can also reduce the carbon footprint. To realize the green machine learning protocols, this book presents different aspects of green machine learning for future communication networks. This book highlights mainly the green machine learning protocols for cellular communication, federated learning-based models, and protocols for Beyond Fifth Generation networks, approaches for cloud-based communications, and Internet-of-Things. This book also highlights the design considerations and challenges for green machine learning protocols for different future applications.
| Author | : Saim Ghafoor |
| Publisher | : CRC Press |
| Total Pages | : 223 |
| Release | : 2023-10-25 |
| Genre | : Computers |
| ISBN | : 1000968928 |
Machine learning has shown tremendous benefits in solving complex network problems and providing situation and parameter prediction. However, heavy resources are required to process and analyze the data, which can be done either offline or using edge computing but also requires heavy transmission resources to provide a timely response. The need here is to provide lightweight machine learning protocols that can process and analyze the data at run time and provide a timely and efficient response. These algorithms have grown in terms of computation and memory requirements due to the availability of large data sets. These models/algorithms also require high levels of resources such as computing, memory, communication, and storage. The focus so far was on producing highly accurate models for these communication networks without considering the energy consumption of these machine learning algorithms. For future scalable and sustainable network applications, efforts are required toward designing new machine learning protocols and modifying the existing ones, which consume less energy, i.e., green machine learning protocols. In other words, novel and lightweight green machine learning algorithms/protocols are required to reduce energy consumption which can also reduce the carbon footprint. To realize the green machine learning protocols, this book presents different aspects of green machine learning for future communication networks. This book highlights mainly the green machine learning protocols for cellular communication, federated learning-based models, and protocols for Beyond Fifth Generation networks, approaches for cloud-based communications, and Internet-of-Things. This book also highlights the design considerations and challenges for green machine learning protocols for different future applications.
| Author | : Gurjit Kaur |
| Publisher | : CRC Press |
| Total Pages | : 301 |
| Release | : 2022-10-31 |
| Genre | : Technology & Engineering |
| ISBN | : 1000761266 |
This book explores all the energy-efficient communication technologies used for various communication systems and every aspect of these systems, such as green electronics, network protocols, handover, codes, antenna, and the role of artificial intelligence and IoT, including the energy management strategies. It identifies the development of sustainable plans and programs at the communication level within the current legislative framework. Features: Gives a fundamental description of the green communications including granularities of green wired and wireless systems. Describes a comprehensive review of innovations, challenges, and opportunities for green communication. Provides guiding principles on how to build the green communication network. Includes a holistic view of both wireless and wired green communication systems with an emphasis on applications and challenges in each area. Suggests various ways of benchmarking and measuring the performance of green communication systems. This book will be of great interest to graduate students and researchers in green technologies, communications, wireless communication, optical communication, underwater communication, microwave and satellite communication, networking, the internet of things, and energy management.
| Author | : Hassan, Jahan |
| Publisher | : IGI Global |
| Total Pages | : 425 |
| Release | : 2024-01-17 |
| Genre | : Computers |
| ISBN | : |
Applications of Machine Learning in UAV Networks presents a pioneering exploration into the symbiotic relationship between machine learning techniques and UAVs. In an age where UAVs are revolutionizing sectors as diverse as agriculture, environmental preservation, security, and disaster response, this meticulously crafted volume offers an analysis of the manifold ways machine learning drives advancements in UAV network efficiency and efficacy. This book navigates through an expansive array of domains, each demarcating a pivotal application of machine learning in UAV networks. From the precision realm of agriculture and its dynamic role in yield prediction to the ecological sensitivity of biodiversity monitoring and habitat restoration, the contours of each domain are vividly etched. These explorations are not limited to the terrestrial sphere; rather, they extend to the pivotal aerial missions of wildlife conservation, forest fire monitoring, and security enhancement, where UAVs adorned with machine learning algorithms wield an instrumental role. Scholars and practitioners from fields as diverse as machine learning, UAV technology, robotics, and IoT networks will find themselves immersed in a confluence of interdisciplinary expertise. The book's pages cater equally to professionals entrenched in agriculture, environmental studies, disaster management, and beyond.
| Author | : Ahmed, Zeinab E. |
| Publisher | : IGI Global |
| Total Pages | : 426 |
| Release | : 2024-04-22 |
| Genre | : Education |
| ISBN | : |
The digital age has ushered in an era where students must be equipped not only with traditional knowledge but also with the skills to navigate an increasingly interconnected and technologically driven world. As traditional teaching methods encounter the complexities of the 21st century, the demand for innovation becomes more apparent. This paves the way for the era of artificial intelligence (AI), a technological frontier that carries the potential to reshape education fundamentally. AI-Enhanced Teaching Methods recognizes the urgency of the ongoing technological shift and delves into an exploration of how AI can be effectively harnessed to redefine the learning experience. The book serves as a guide for educators, offering insights into navigating between conventional teaching methodologies and the possibilities presented by AI. It provides an understanding of AI's role in education, covering topics from machine learning to natural language processing. Ethical considerations, including privacy and bias, are thoroughly addressed with thoughtful solutions as well. Additionally, the book provides valuable support for administrators, aiding in the integration of these technologies into existing curricula.
| Author | : Alan Pak Tao Lau |
| Publisher | : Academic Press |
| Total Pages | : 404 |
| Release | : 2022-02-10 |
| Genre | : Technology & Engineering |
| ISBN | : 0323852289 |
Machine Learning for Future Fiber-Optic Communication Systems provides a comprehensive and in-depth treatment of machine learning concepts and techniques applied to key areas within optical communications and networking, reflecting the state-of-the-art research and industrial practices. The book gives knowledge and insights into the role machine learning-based mechanisms will soon play in the future realization of intelligent optical network infrastructures that can manage and monitor themselves, diagnose and resolve problems, and provide intelligent and efficient services to the end users. With up-to-date coverage and extensive treatment of various important topics related to machine learning for fiber-optic communication systems, this book is an invaluable reference for photonics researchers and engineers. It is also a very suitable text for graduate students interested in ML-based signal processing and networking. Discusses the reasons behind the recent popularity of machine learning (ML) concepts in modern optical communication networks and the why/where/how ML can play a unique role Presents fundamental ML techniques like artificial neural networks (ANNs), support vector machines (SVMs), K-means clustering, expectation-maximization (EM) algorithm, principal component analysis (PCA), independent component analysis (ICA), reinforcement learning, and more Covers advanced deep learning (DL) methods such as deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs) Individual chapters focus on ML applications in key areas of optical communications and networking
| Author | : Alagan Anpalagan |
| Publisher | : Academic Press |
| Total Pages | : 815 |
| Release | : 2012-11-20 |
| Genre | : Technology & Engineering |
| ISBN | : 012415882X |
This book gives a comprehensive guide on the fundamental concepts, applications, algorithms, protocols, new trends and challenges, and research results in the area of Green Information and Communications Systems. It is an invaluable resource giving knowledge on the core and specialized issues in the field, making it highly suitable for both the new and experienced researcher in this area. Key Features: Core research topics of green information and communication systems are covered from a network design perspective, giving both theoretical and practical perspectives Provides a unified covering of otherwise disperse selected topics on green computing, information, communication and networking Includes a set of downloadable PowerPoint slides and glossary of terms for each chapter A ‘whose-who’ of international contributors Extensive bibliography for enhancing further knowledge Coverage includes: Smart grid technologies and communications Spectrum management Cognitive and autonomous radio systems Computing and communication architectures Data centres Distributed networking Cloud computing Next generation wireless communication systems 4G access networking Optical core networks Cooperation transmission Security and privacy Core research topics of green information and communication systems are covered from a network design perspective, giving both a theoretical and practical perspective A ‘whose-who’ of international contributors Extensive bibliography for enhancing further knowledge
| Author | : Rajshree Srivastava |
| Publisher | : CRC Press |
| Total Pages | : 213 |
| Release | : 2020-11-19 |
| Genre | : Technology & Engineering |
| ISBN | : 1000207595 |
Green Information and Communication Systems for a Sustainable Future covers the fundamental concepts, applications, algorithms, protocols, new trends, challenges, and research results in the area of Green Information and Communication Systems. This book provides the reader with up-to-date information on core and specialized issues, making it highly suitable for both the novice and the experienced researcher in the field. The book covers theoretical and practical perspectives on network design. It includes how green ICT initiatives and applications can play a major role in reducing CO2 emissions, and focuses on industry and how it can promote awareness and implementation of Green ICT. The book discusses scholarship and research in green and sustainable IT for business and organizations and uses the power of IT to usher sustainability into other parts of an organization. Business and management educators, management researchers, doctoral scholars, university teaching personnel and policy makers as well as members of higher academic research organizations will all discover this book to be an indispensable guide to Green Information and Communication Systems. It will also serve as a key resource for Industrial and Management training organizations all over the world.
| Author | : Mangesh M. Ghonge |
| Publisher | : CRC Press |
| Total Pages | : 357 |
| Release | : 2021-12-30 |
| Genre | : Computers |
| ISBN | : 1000504069 |
This book offers a comprehensive overview of basic communication and networking technologies. It focuses on emerging technologies, such as Software-Defined Network (SDN)-based ad hoc networks, 5G, Machine Learning, and Deep Learning solutions for communication and networking, Cloud Computing, etc. It also includes discussions on practical and innovative applications, including Network Security, Smart Cities, e-health, and Intelligent Systems. Future Trends in 5G and 6G: Challenges, Architecture, and Applications addresses several key issues in SDN energy-efficient systems, the Internet of Things, Big Data, Cloud Computing and Virtualization, Machine Learning, Deep Learning, Cryptography, and 6G wireless technology and its future. It provides students, researchers, and practicing engineers with an expert guide to the fundamental concepts, challenges, architecture, applications, and state-of-the-art developments in communication and networking.
| Author | : Fa-Long Luo |
| Publisher | : John Wiley & Sons |
| Total Pages | : 490 |
| Release | : 2020-02-10 |
| Genre | : Technology & Engineering |
| ISBN | : 1119562252 |
A comprehensive review to the theory, application and research of machine learning for future wireless communications In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities. Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author – a noted expert on the topic – covers a wide range of topics including system architecture and optimization, physical-layer and cross-layer processing, air interface and protocol design, beamforming and antenna configuration, network coding and slicing, cell acquisition and handover, scheduling and rate adaption, radio access control, smart proactive caching and adaptive resource allocations. Uniquely organized into three categories: Spectrum Intelligence, Transmission Intelligence and Network Intelligence, this important resource: Offers a comprehensive review of the theory, applications and current developments of machine learning for wireless communications and networks Covers a range of topics from architecture and optimization to adaptive resource allocations Reviews state-of-the-art machine learning based solutions for network coverage Includes an overview of the applications of machine learning algorithms in future wireless networks Explores flexible backhaul and front-haul, cross-layer optimization and coding, full-duplex radio, digital front-end (DFE) and radio-frequency (RF) processing Written for professional engineers, researchers, scientists, manufacturers, network operators, software developers and graduate students, Machine Learning for Future Wireless Communications presents in 21 chapters a comprehensive review of the topic authored by an expert in the field.
