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COMMUNICATION NETWORKS AND SERVICE MANAGEMENT IN THE ERA OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING Discover the impact that new technologies are having on communication systems with this up-to-date and one-stop resource Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning delivers a comprehensive overview of the impact of artificial intelligence (AI) and machine learning (ML) on service and network management. Beginning with a fulsome description of ML and AI, the book moves on to discuss management models, architectures, and frameworks. The authors also explore how AI and ML can be used in service management functions like the generation of workload profiles, service provisioning, and more. The book includes a handpicked selection of applications and case studies, as well as a treatment of emerging technologies the authors predict could have a significant impact on network and service management in the future. Statistical analysis and data mining are also discussed, particularly with respect to how they allow for an improvement of the management and security of IT systems and networks. Readers will also enjoy topics like: A thorough introduction to network and service management, machine learning, and artificial intelligence An exploration of artificial intelligence and machine learning for management models, including autonomic management, policy-based management, intent based ­management, and network virtualization-based management Discussions of AI and ML for architectures and frameworks, including cloud ­systems, software defined networks, 5G and 6G networks, and Edge/Fog networks An examination of AI and ML for service management, including the automatic ­generation of workload profiles using unsupervised learning Perfect for information and communications technology educators, Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning will also earn a place in the libraries of engineers and professionals who seek a structured reference on how the emergence of artificial intelligence and machine learning techniques is affecting service and network management.
This book provides a comprehensive introduction to the underlying theory, design techniques and analytical results of wireless communication networks, focusing on the core principles of wireless network design. It elaborates the network utility maximization (NUM) theory with applications in resource allocation of wireless networks, with a central aim of design and the QoS guarantee. It presents and discusses state-of-the-art developments in resource allocation and performance optimization in wireless communication networks. It provides an overview of the general background including the basic wireless communication networks and the relevant protocols, architectures, methods and algorithms.
This book considers advanced real-time optimisation methods for 5G and beyond networks. The authors discuss the fundamentals, technologies, practical questions and challenges around real-time optimisation of 5G and beyond communications, providing insights into relevant theories, models and techniques.
The purpose of this book is to provide tools for a better understanding of the fundamental tradeo?s and interdependencies in wireless networks, with the goal of designing resource allocation strategies that exploit these int- dependencies to achieve signi?cant performance gains. Two facts prompted us to write it: First, future wireless applications will require a fundamental understanding of the design principles and control mechanisms in wireless networks. Second, the complexity of the network problems simply precludes the use of engineering common sense alone to identify good solutions, and so mathematics becomes the key avenue to cope with central technical problems in the design of wireless networks. In this book, two ?elds of mathematics play a central role: Perron-Frobenius theory for non-negative matrices and optimization theory. This book is a revised and expanded version of the research monograph “Resource Allocation in Wireless Networks” that was published as Lecture Notes in Computer Sciences (LNCS 4000) in 2006. Although the general structure has remained unchanged to a large extent, the book contains - merous additional results and more detailed discussion. For instance, there is a more extensive treatment of general nonnegative matrices and interf- ence functions that are described by an axiomatic model. Additional material on max-min fairness, proportional fairness, utility-based power control with QoS (quality of service) support and stochastic power control has been added.
There have been recent advancements in wireless network technologies such as wireless virtualization to accommodate the exponential growth in demand, as well as to increase energy and infrastructure efficiencies. This SpringerBrief discusses the user-association and resource-allocation aspects in Virtualized Wireless Networks (VWNs) and highlights key technology innovations to meet their requirements. Various issues in practical implementation of VWNs are discussed along with potential techniques such as Massive MIMO, Cloud-Radio Access Network (C-RAN), and non-orthogonal multiple access (NOMA). This SpringerBrief will target researchers and professionals working on current and next-generation wireless networks. The content is also valuable for advanced-level students interested in wireless communications and signal processing for communications.
The first book on Cloud Radio Access Networks (C-RANs), covering fundamental theory, current techniques, and potential applications.
Scientific Study from the year 2016 in the subject Engineering - Communication Technology, Mahalingam College of Engineering and Technology, language: English, abstract: The future Wireless Communication Systems (WCS) are supposed to provide high data rate to support personal and multimedia communications irrespective of the users' mobility and location. These services include heterogeneous classes of traffics such as voice, file transfer, web browsing, wireless multimedia, teleconferencing, and interactive games. In recent years, data and multimedia services have become important in wireless communications. As a result, bandwidth requirement and number of users become delicate problems. To support high data rate requirement for future WCS, it is essential to efficiently allocate the limited resources. The major challenges are the dynamic nature of wireless channel, limited resources such as power, frequency spectrum, and diversified Quality of Service (QoS) requirements. Orthogonal Frequency Division Multiplexing (OFDM) is a special case of multicarrier transmission that supports high data rate operation. OFDM is a modulation and multiplexing technique appropriate for current and future wireless networks. OFDM divides the available bandwidth into a number of parallel independent orthogonal subchannels and their bandwidth is much less than the coherence bandwidth of the channel. The wide band frequency selective fading channel is converted into several narrow band flat fading channels. OFDM is an excellent method to overcome multipath fading effects. One of the goals of WCS is to enhance the capacity of the channel. Multiple Access Technique (MAT) permits several mobile users to share the given bandwidth in an effective way. Basically there are four multiple access techniques available namely, Time Division Multiple Access (TDMA), Frequency Division Multiple access (FDMA), Code Division Multiple Access (CDMA) and Space Division Multiple Access (SDMA). MAT is employ
Machine Learning Approach for Cloud Data Analytics in IoT The book covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications Sustainable computing paradigms like cloud and fog are capable of handling issues related to performance, storage and processing, maintenance, security, efficiency, integration, cost, energy and latency in an expeditious manner. In order to expedite decision-making involved in the complex computation and processing of collected data, IoT devices are connected to the cloud or fog environment. Since machine learning as a service provides the best support in business intelligence, organizations have been making significant investments in this technology. Machine Learning Approach for Cloud Data Analytics in IoT elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.
ICT technologies have contributed to the advances in wireless systems, which provide seamless connectivity for worldwide communication. The growth of interconnected devices and the need to store, manage, and process the data from them has led to increased research on the intersection of the internet of things and cloud computing. The Handbook of Research on the IoT, Cloud Computing, and Wireless Network Optimization is a pivotal reference source that provides the latest research findings and solutions for the design and augmentation of wireless systems and cloud computing. The content within this publication examines data mining, machine learning, and software engineering, and is designed for IT specialists, software engineers, researchers, academicians, industry professionals, and students.
This book introduces recent wireless technologies and their impact on recent trends, applications, and opportunities. It explores the latest 6G, IoT, and Blockchain techniques with AI and evolutionary applications, showing how digital integration can be used to serve society. It explores the most important aspects of modern technologies, providing insights into the newest 6G technology and practices; covering the roles, responsibilities, and impact of IoT, 6G, and Blockchain practices to sustain the world economy. This book highlights the roles, responsibilities, and impact of IoT, 6G, and Blockchain and its practices. By describing the implementation strategies for Blockchain, IoT, and 6G, this book focuses on technologies related to the advancement in wireless ad-hoc networks and the current sustainability practices used in IoT. It offers popular use cases and case studies related to 6G, IoT, and Blockchain to provide a better understanding and covers the global approach towards the convergence of 6G, IoT, and Blockchain along with recent applications and future potential. The book is a reference for those working with 6G, IoT, AI, and its related application areas. Students at both the UG and PG levels in various departments such as manufacturing, electronics, telecommunications, computer science, other engineering fields, and information technology will be interested in this book. It is ideally designed for use by technology development, academicians, data scientists, industry professionals, researchers, and students.