Download or read book Sequential Learning and Decision Making in Wireless Resource Management written by Rong Zheng and published by Springer. This book was released on 2017-01-05 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book lays out the theoretical foundation of the so-called multi-armed bandit (MAB) problems and puts it in the context of resource management in wireless networks. Part I of the book presents the formulations, algorithms and performance of three forms of MAB problems, namely, stochastic, Markov and adversarial. Covering all three forms of MAB problems makes this book unique in the field. Part II of the book provides detailed discussions of representative applications of the sequential learning framework in cognitive radio networks, wireless LANs and wireless mesh networks. Both individuals in industry and those in the wireless research community will benefit from this comprehensive and timely treatment of these topics. Advanced-level students studying communications engineering and networks will also find the content valuable and accessible.

Download or read book Resource Management for Heterogeneous Wireless Networks written by Amila Tharaperiya Gamage and published by Springer. This book was released on 2017-08-18 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an in-depth discussion on how to efficiently manage resources of heterogeneous wireless networks and how to design resource allocation algorithms to suit real world conditions. Efficiently managing resources of the networks is more crucial now, than ever before, to meet users’ rapidly increasing demand for higher data rates, better quality-of-service (QoS) and seamless coverage. Some of the techniques that can be incorporated within heterogeneous wireless networks to achieve this objective are interworking of the networks, user multi-homing and device-to-device (D2D) communication. Designing resource allocation algorithms to suit real world conditions is also important, as the algorithms should be deployable and perform well in real networks. For example, two of the conditions considered in this book are resource allocation intervals of different networks are different and small cell base stations have limited computational capacity. To address the first condition, resource allocation algorithms for interworking systems are designed to allocate resources of different networks at different time-scales. To address the second condition, resource allocation algorithms are designed to be able to run at cloud computing servers. More of such conditions, algorithms designed to suit these conditions, modeling techniques for various networks and performance analysis of the algorithms are discussed in the book. This book concludes with a discussion on the future research directions on the related fields of study. Advanced-level students focused on communication and networking will use this book as a study guide. Researchers and experts in the fields of networking, converged networks, small-cell networks, resource management, and interference management, as well as consultants working in network planning and optimization and managers, executives and network architects working in the networking industry will also find this book useful as a reference.

Download or read book Artificial Intelligent Techniques for Wireless Communication and Networking written by R. Kanthavel and published by John Wiley & Sons. This book was released on 2022-03-22 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: ARTIFICIAL INTELLIGENT TECHNIQUES FOR WIRELESS COMMUNICATION AND NETWORKING The 20 chapters address AI principles and techniques used in wireless communication and networking and outline their benefit, function, and future role in the field. Wireless communication and networking based on AI concepts and techniques are explored in this book, specifically focusing on the current research in the field by highlighting empirical results along with theoretical concepts. The possibility of applying AI mechanisms towards security aspects in the communication domain is elaborated; also explored is the application side of integrated technologies that enhance AI-based innovations, insights, intelligent predictions, cost optimization, inventory management, identification processes, classification mechanisms, cooperative spectrum sensing techniques, ad-hoc network architecture, and protocol and simulation-based environments. Audience Researchers, industry IT engineers, and graduate students working on and implementing AI-based wireless sensor networks, 5G, IoT, deep learning, reinforcement learning, and robotics in WSN, and related technologies.

Download or read book Towards User Centric Intelligent Network Selection in 5G Heterogeneous Wireless Networks written by Zhiyong Du and published by Springer Nature. This book was released on 2019-11-06 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents reinforcement learning (RL) based solutions for user-centric online network selection optimization. The main content can be divided into three parts. The first part (chapter 2 and 3) focuses on how to learning the best network when QoE is revealed beyond QoS under the framework of multi-armed bandit (MAB). The second part (chapter 4 and 5) focuses on how to meet dynamic user demand in complex and uncertain heterogeneous wireless networks under the framework of markov decision process (MDP). The third part (chapter 6 and 7) focuses on how to meet heterogeneous user demand for multiple users inlarge-scale networks under the framework of game theory. Efficient RL algorithms with practical constraints and considerations are proposed to optimize QoE for realizing intelligent online network selection for future mobile networks. This book is intended as a reference resource for researchers and designers in resource management of 5G networks and beyond.

Download or read book Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning written by Nur Zincir-Heywood and published by John Wiley & Sons. This book was released on 2021-09-03 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Advancing Computational Intelligence Techniques for Security Systems Design written by Uzzal Sharma and published by CRC Press. This book was released on 2022-08-24 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: Security systems have become an integral part of the building and large complex setups, and intervention of the computational intelligence (CI) paradigm plays an important role in security system architecture. This book covers both theoretical contributions and practical applications in security system design by applying the Internet of Things (IoT) and CI. It further explains the application of IoT in the design of modern security systems and how IoT blended with computational intel- ligence can make any security system improved and realizable. Key features: Focuses on the computational intelligence techniques of security system design Covers applications and algorithms of discussed computational intelligence techniques Includes convergence-based and enterprise integrated security systems with their applications Explains emerging laws, policies, and tools affecting the landscape of cyber security Discusses application of sensors toward the design of security systems This book will be useful for graduate students and researchers in electrical, computer engineering, security system design and engineering.

Download or read book Learning Methods for Sequential Decision Making with Imperfect Representations written by Shivaram Kalyanakrishnan and published by . This book was released on 2011 with total page 658 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sequential decision making from experience, or reinforcement learning (RL), is a paradigm that is well-suited for agents seeking to optimize long-term gain as they carry out sensing, decision, and action in an unknown environment. RL tasks are commonly formulated as Markov Decision Problems (MDPs). Learning in finite MDPs enjoys several desirable properties, such as convergence, sample-efficiency, and the ability to realize optimal behavior. Key to achieving these properties is access to a perfect representation, under which the state and action sets of the MDP can be enumerated. Unfortunately, RL tasks encountered in the real world commonly suffer from state aliasing, and nearly always they demand generalization. As a consequence, learning in practice invariably amounts to learning with imperfect representations. In this dissertation, we examine the effect of imperfect representations on different classes of learning methods, and introduce techniques to improve their practical performance. We make four main contributions. First we introduce “parameterized learning problems”, a novel experimental methodology facilitating the systematic control of representational aspects such as state aliasing and generalization. Applying this methodology, we compare the class of on-line value function-based (VF) methods with the class of policy search (PS) methods. Results indicate clear patterns in the effects of representation on these classes of methods. Our second contribution is a deeper analysis of the limits imposed by representations on VF methods; specifically we provide a plausible explanation for the relatively poor performance of these methods on Tetris, the popular video game. The third major contribution of this dissertation is a formal study of the “subset selection” problem in multi-armed bandits. This problem, which directly affects the sample-efficiency of several commonly-used PS methods, also finds application in areas as diverse as industrial engineering and on-line advertising. We present new algorithms for subset selection and bound their performance under different evaluation criteria. Under a PAC setting, our sample complexity bounds indeed improve upon existing ones. As its fourth contribution, this dissertation introduces two hybrid learning architectures for combining the strengths of VF and PS methods. Under one architecture, these methods are applied in sequence; under the other, they are applied to separate components of a compound task. We demonstrate the effectiveness of these methods on a complex simulation of robot soccer. In sum, this dissertation makes philosophical, analytical, and methodological contributions towards the development of robust and automated learning methods for sequential decision making with imperfect representations

Download or read book Proceedings of ELM 2014 Volume 2 written by Jiuwen Cao and published by Springer. This book was released on 2014-12-09 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains some selected papers from the International Conference on Extreme Learning Machine 2014, which was held in Singapore, December 8-10, 2014. This conference brought together the researchers and practitioners of Extreme Learning Machine (ELM) from a variety of fields to promote research and development of “learning without iterative tuning”. The book covers theories, algorithms and applications of ELM. It gives the readers a glance of the most recent advances of ELM.

Download or read book Search and Classification Using Multiple Autonomous Vehicles written by Yue Wang and published by Springer Science & Business Media. This book was released on 2012-04-02 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Search and Classification Using Multiple Autonomous Vehicles provides a comprehensive study of decision-making strategies for domain search and object classification using multiple autonomous vehicles (MAV) under both deterministic and probabilistic frameworks. It serves as a first discussion of the problem of effective resource allocation using MAV with sensing limitations, i.e., for search and classification missions over large-scale domains, or when there are far more objects to be found and classified than there are autonomous vehicles available. Under such scenarios, search and classification compete for limited sensing resources. This is because search requires vehicle mobility while classification restricts the vehicles to the vicinity of any objects found. The authors develop decision-making strategies to choose between these competing tasks and vehicle-motion-control laws to achieve the proposed management scheme. Deterministic Lyapunov-based, probabilistic Bayesian-based, and risk-based decision-making strategies and sensor-management schemes are created in sequence. Modeling and analysis include rigorous mathematical proofs of the proposed theorems and the practical consideration of limited sensing resources and observation costs. A survey of the well-developed coverage control problem is also provided as a foundation of search algorithms within the overall decision-making strategies. Applications in both underwater sampling and space-situational awareness are investigated in detail. The control strategies proposed in each chapter are followed by illustrative simulation results and analysis. Academic researchers and graduate students from aerospace, robotics, mechanical or electrical engineering backgrounds interested in multi-agent coordination and control, in detection and estimation or in Bayes filtration will find this text of interest.

Download or read book Dynamic Spectrum Management written by Ying-Chang Liang and published by Springer Nature. This book was released on 2019-11-02 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book, authored by a world-leading researcher in this field, describes fundamentals of dynamic spectrum management, provides a systematic overview on the enabling technologies covering cognitive radio, blockchain, and artificial intelligence, and offers valuable guidance for designing advanced wireless communications systems. This book is intended for a broad range of readers, including students and professionals in this field, as well as radio spectrum policy makers.

Download or read book Context Aware Decision Making in Wireless Networks Optimization and Machine Learning Approaches written by Sabrina Klos and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multimedia Streaming in SDN NFV and 5G Networks written by Alcardo Barakabitze and published by John Wiley & Sons. This book was released on 2022-12-06 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multimedia Streaming in SDN/NFV and 5G Networks A comprehensive overview of Quality of Experience control and management of multimedia services in future networks In Multimedia Streaming in SDN/NFV and 5G Networks, renowned researchers deliver a high-level exploration of Quality of Experience (QoE) control and management solutions for multimedia services in future softwarized and virtualized 5G networks. The book offers coverage of network softwarization and virtualization technologies, including SDN, NFV, MEC, and Fog/Cloud Computing, as critical elements for the management of multimedia services in future networks, like 5G and 6G networks and beyond. Providing a fulsome examination of end-to-end QoE control and management solutions in softwarized and virtualized networks, the book concludes with discussions of probable future challenges and research directions in emerging multimedia services and applications, 5G network management and orchestration, network slicing and collaborative service management of multimedia services in softwarized networks, and QoE-oriented business models. The distinguished authors also explore: Thorough introductions to 5G networks, including definitions and requirements, as well as Quality of Experience management of multimedia streaming services Comprehensive explorations of multimedia streaming services over the internet and network softwarization and virtualization in future networks Practical discussions of QoE management using SDN and NFV in future networks, as well as QoE management of multimedia services in emerging architectures, including MEC, ICN, and Fog/Cloud Computing In-depth examinations of QoE in emerging applications, 5G network slicing architectures and implementations, and 5G network slicing orchestration and resource management Perfect for researchers and engineers in multimedia services and telecoms, Multimedia Streaming in SDN/NFV and 5G Networks will also earn a place in the libraries of graduate and senior undergraduate students with interests in computer science, communication engineering, and telecommunication systems.

Download or read book Interference and Resource Management in Heterogeneous Wireless Networks written by Jiandong Li and published by Artech House. This book was released on 2017-11-30 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: This authoritative resource offers a comprehensive overview of heterogeneous wireless networks, small cells, and device-to-device (D2D) communications. The book provides insight into network modeling and performance analysis of heterogeneous wireless networks. Interference management framework and design issues are covered as well as details about resource mobility, channel models, and typical and statistical interference modeling. This resource explains leveraging resource heterogeneity in interference mitigation and presents the challenges and feasible solutions for concurrent transmission. Moreover, complete coverage of interference alignment in MIMO heterogeneous networks for both downlink and uplink is presented. This book provides performance results for an ideal partially connected interference network as well as a practical heterogeneous network. Readers find practical guidance for LTE and LTE-Advanced as well as 5G in this resource. New techniques and designs for heterogeneous wireless networks are included.

Download or read book New Directions in Wireless Communications Systems written by Athanasios G. Kanatas and published by CRC Press. This book was released on 2017-10-16 with total page 563 pages. Available in PDF, EPUB and Kindle. Book excerpt: Beyond 2020, wireless communication systems will have to support more than 1,000 times the traffic volume of today's systems. This extremely high traffic load is a major issue faced by 5G designers and researchers. This challenge will be met by a combination of parallel techniques that will use more spectrum more flexibly, realize higher spectral efficiency, and densify cells. Novel techniques and paradigms must be developed to meet these goals. The book addresses diverse key-point issues of next-generation wireless communications systems and identifies promising solutions. The book's core is concentrated to techniques and methods belonging to what is generally called radio access network.

Download or read book Reinforcement Learning for Reconfigurable Intelligent Surfaces written by Alice Faisal and published by Springer Nature. This book was released on with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Artificial Intelligence for 6G written by Haesik Kim and published by Springer Nature. This book was released on 2022-03-29 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook introduces Artificial Intelligence (AI) techniques for wireless communications and networks, helping readers to find solutions for communications and network problems using AI. Artificial Intelligence for 6G introduces, in a step-by-step manner, AI techniques such as: unsupervised learning; supervised learning; reinforcement learning; and deep learning. It explains how these techniques can be used for wireless communications and network systems, particularly in designing and optimizing 6G networks. This book is at the forefront of 6G research, and will be of interest internationally, to graduate students, academics, engineers, and developers who are focused on future development of network systems and mobile communications.

Download or read book Intelligent Communication Networks written by Rajarshi Mahapatra and published by CRC Press. This book was released on 2024-06-06 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the advent of Big Data, conventional communication networks are often limited in their inability to handle complex and voluminous data and information as far as effective processing, transmission, and reception are concerned. This book discusses the evolution of computational intelligence techniques in handling intelligent communication networks. Provides a detailed theoretical foundation of machine learning and computational intelligence algorithms Highlights the state of art machine learning-based solutions for communication networks Presents video demonstrations and code snippets on each chapter for easy understanding of the concepts Discusses applications including resource allocation, spectrum management, channel estimation, and physical layer of wireless networks Demonstrates applications of machine learning techniques for optical networks The text is primarily intended for senior undergraduate and graduate students and academic researchers in fields of electrical engineering, electronics and communication engineering, and computer engineering.