Wireless Edge Caching

Wireless Edge Caching PDF Author: Thang X. Vu
Publisher: Cambridge University Press
ISBN: 1108574211
Category : Technology & Engineering
Languages : en
Pages : 431

Get Book Here

Book Description
Understand both uncoded and coded caching techniques in future wireless network design. Expert authors present new techniques that will help you to improve backhaul, load minimization, deployment cost reduction, security, energy efficiency and the quality of the user experience. Covering topics from high-level architectures to specific requirement-oriented caching design and analysis, including big-data enabled caching, caching in cloud-assisted 5G networks, and security, this is an essential resource for academic researchers, postgraduate students and engineers working in wireless communications.

Wireless Edge Caching

Wireless Edge Caching PDF Author: Thang X. Vu
Publisher: Cambridge University Press
ISBN: 1108574211
Category : Technology & Engineering
Languages : en
Pages : 431

Get Book Here

Book Description
Understand both uncoded and coded caching techniques in future wireless network design. Expert authors present new techniques that will help you to improve backhaul, load minimization, deployment cost reduction, security, energy efficiency and the quality of the user experience. Covering topics from high-level architectures to specific requirement-oriented caching design and analysis, including big-data enabled caching, caching in cloud-assisted 5G networks, and security, this is an essential resource for academic researchers, postgraduate students and engineers working in wireless communications.

Wireless Edge Caching

Wireless Edge Caching PDF Author: Thang X. Vu
Publisher: Cambridge University Press
ISBN: 1108480837
Category : Computers
Languages : en
Pages : 431

Get Book Here

Book Description
Discover the latest research results for both uncoded and coded caching techniques in future wireless network design.

Mobile Edge Computing

Mobile Edge Computing PDF Author: Yan Zhang
Publisher: Springer Nature
ISBN: 3030839443
Category : Computers
Languages : en
Pages : 123

Get Book Here

Book Description
This is an open access book. It offers comprehensive, self-contained knowledge on Mobile Edge Computing (MEC), which is a very promising technology for achieving intelligence in the next-generation wireless communications and computing networks.The book starts with the basic concepts, key techniques and network architectures of MEC. Then, we present the wide applications of MEC, including edge caching, 6G networks, Internet of Vehicles, and UAVs. In the last part, we present new opportunities when MEC meets blockchain, Artificial Intelligence, and distributed machine learning (e.g., federated learning). We also identify the emerging applications of MEC in pandemic, industrial Internet of Things and disaster management.The book allows an easy cross-reference owing to the broad coverage on both the principle and applications of MEC. The book is written for people interested in communications and computer networks at all levels. The primary audience includes senior undergraduates, postgraduates, educators, scientists, researchers, developers, engineers, innovators and research strategists.

Machine Learning for Future Wireless Communications

Machine Learning for Future Wireless Communications PDF Author: Fa-Long Luo
Publisher: John Wiley & Sons
ISBN: 1119562252
Category : Technology & Engineering
Languages : en
Pages : 490

Get Book Here

Book Description
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.

Federated Learning Over Wireless Edge Networks

Federated Learning Over Wireless Edge Networks PDF Author: Wei Yang Bryan Lim
Publisher: Springer Nature
ISBN: 3031078381
Category : Technology & Engineering
Languages : en
Pages : 175

Get Book Here

Book Description
This book first presents a tutorial on Federated Learning (FL) and its role in enabling Edge Intelligence over wireless edge networks. This provides readers with a concise introduction to the challenges and state-of-the-art approaches towards implementing FL over the wireless edge network. Then, in consideration of resource heterogeneity at the network edge, the authors provide multifaceted solutions at the intersection of network economics, game theory, and machine learning towards improving the efficiency of resource allocation for FL over the wireless edge networks. A clear understanding of such issues and the presented theoretical studies will serve to guide practitioners and researchers in implementing resource-efficient FL systems and solving the open issues in FL respectively.

Software Defined Mobile Networks (SDMN)

Software Defined Mobile Networks (SDMN) PDF Author: Madhusanka Liyanage
Publisher: John Wiley & Sons
ISBN: 1118900278
Category : Technology & Engineering
Languages : en
Pages : 440

Get Book Here

Book Description
This book describes the concept of a Software Defined Mobile Network (SDMN), which will impact the network architecture of current LTE (3GPP) networks. SDN will also open up new opportunities for traffic, resource and mobility management, as well as impose new challenges on network security. Therefore, the book addresses the main affected areas such as traffic, resource and mobility management, virtualized traffics transportation, network management, network security and techno economic concepts. Moreover, a complete introduction to SDN and SDMN concepts. Furthermore, the reader will be introduced to cutting-edge knowledge in areas such as network virtualization, as well as SDN concepts relevant to next generation mobile networks. Finally, by the end of the book the reader will be familiar with the feasibility and opportunities of SDMN concepts, and will be able to evaluate the limits of performance and scalability of these new technologies while applying them to mobile broadb and networks.

High Performance Browser Networking

High Performance Browser Networking PDF Author: Ilya Grigorik
Publisher: "O'Reilly Media, Inc."
ISBN: 1449344720
Category :
Languages : en
Pages : 420

Get Book Here

Book Description
How prepared are you to build fast and efficient web applications? This eloquent book provides what every web developer should know about the network, from fundamental limitations that affect performance to major innovations for building even more powerful browser applications—including HTTP 2.0 and XHR improvements, Server-Sent Events (SSE), WebSocket, and WebRTC. Author Ilya Grigorik, a web performance engineer at Google, demonstrates performance optimization best practices for TCP, UDP, and TLS protocols, and explains unique wireless and mobile network optimization requirements. You’ll then dive into performance characteristics of technologies such as HTTP 2.0, client-side network scripting with XHR, real-time streaming with SSE and WebSocket, and P2P communication with WebRTC. Deliver superlative TCP, UDP, and TLS performance Speed up network performance over 3G/4G mobile networks Develop fast and energy-efficient mobile applications Address bottlenecks in HTTP 1.x and other browser protocols Plan for and deliver the best HTTP 2.0 performance Enable efficient real-time streaming in the browser Create efficient peer-to-peer videoconferencing and low-latency applications with real-time WebRTC transports

Integrated Networking, Caching, and Computing

Integrated Networking, Caching, and Computing PDF Author: F. Richard Yu
Publisher: CRC Press
ISBN: 1351611240
Category : Computers
Languages : en
Pages : 251

Get Book Here

Book Description
This book features the major research advances on integrated networking, caching, and computing. Information-centric networking-based caching is one of the promising techniques for future networks. The cloud computing paradigm has been widely adopted to enable convenient, on-demand network access to a shared pool of configurable computing resources. In addition, fog/edge computing is proposed to deploy computing resources closer to end devices. From the perspective of applications, network, cache and compute are underlying enabling resources. How to manage, control and optimize these resources can have significant impacts on application performance.

Handbook of Research on the IoT, Cloud Computing, and Wireless Network Optimization

Handbook of Research on the IoT, Cloud Computing, and Wireless Network Optimization PDF Author: Singh, Surjit
Publisher: IGI Global
ISBN: 1522573364
Category : Computers
Languages : en
Pages : 663

Get Book Here

Book Description
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.

Deep Reinforcement Learning for Wireless Networks

Deep Reinforcement Learning for Wireless Networks PDF Author: F. Richard Yu
Publisher: Springer
ISBN: 3030105466
Category : Technology & Engineering
Languages : en
Pages : 78

Get Book Here

Book Description
This Springerbrief presents a deep reinforcement learning approach to wireless systems to improve system performance. Particularly, deep reinforcement learning approach is used in cache-enabled opportunistic interference alignment wireless networks and mobile social networks. Simulation results with different network parameters are presented to show the effectiveness of the proposed scheme. There is a phenomenal burst of research activities in artificial intelligence, deep reinforcement learning and wireless systems. Deep reinforcement learning has been successfully used to solve many practical problems. For example, Google DeepMind adopts this method on several artificial intelligent projects with big data (e.g., AlphaGo), and gets quite good results.. Graduate students in electrical and computer engineering, as well as computer science will find this brief useful as a study guide. Researchers, engineers, computer scientists, programmers, and policy makers will also find this brief to be a useful tool.