Trådløs teknologi (WAP)

This book investigates compressive sensing techniques to provide a robust and general framework for network data analytics. The goal is to introduce a compressive sensing framework for missing data interpolation, anomaly detection, data segmentation and activity recognition, and to demonstrate its benefits. Chapter 1 introduces compressive sensing, including its definition, limitation, and how it supports different network analysis applications. Chapter 2 demonstrates the feasibility of compressive sensing in network analytics, the authors we apply it to detect anomalies in the customer care call dataset from a Tier 1 ISP in the United States. A regression-based model is applied to find the relationship between calls and events. The authors illustrate that compressive sensing is effective in identifying important factors and can leverage the low-rank structure and temporal stability to improve the detection accuracy. Chapter 3  discusses that there are several challenges in applying compressive sensing to real-world data. Understanding the reasons behind the challenges is important for designing methods and mitigating their impact. The authors analyze a wide range of real-world traces. The analysis demonstrates that there are different factors that contribute to the violation of the low-rank property in real data. In particular, the authors find that (1) noise, errors, and anomalies, and (2) asynchrony in the time and frequency domains lead to network-induced ambiguity and can easily cause low-rank matrices to become higher-ranked. To address the problem of noise, errors and anomalies in Chap. 4, the authors propose a robust compressive sensing technique. It explicitly accounts for anomalies by decomposing real-world data represented in matrix form into a low-rank matrix, a sparse anomaly matrix, an error term and a small noise matrix. Chapter 5 addresses the problem of lack of synchronization, and the authors propose a data-driven synchronization algorithm. It can eliminate misalignment while taking into account the heterogeneity of real-world data in both time and frequency domains. The data-driven synchronization can be applied to any compressive sensing technique and is general to any real-world data. The authors illustrates that the combination of the two techniques can reduce the ranks of real-world data, improve the effectiveness of compressive sensing and have a wide range of applications. The networks are constantly generating a wealth of rich and diverse information. This information creates exciting opportunities for network analysis and provides insight into the complex interactions between network entities. However, network analysis often faces the problems of (1) under-constrained, where there is too little data due to feasibility and cost issues in collecting data, or (2) over-constrained, where there is too much data, so the analysis becomes unscalable. Compressive sensing is an effective technique to solve both problems. It utilizes the underlying data structure for analysis. Specifically, to solve the under-constrained problem, compressive sensing technologies can be applied to reconstruct the missing elements or predict the future data.  Also, to solve the over-constraint problem, compressive sensing technologies can be applied to identify significant elementsTo support compressive sensing in network data analysis, a robust and general framework is needed to support diverse applications. Yet this can be challenging for real-world data where noise, anomalies and lack of synchronization are common. First, the number of unknowns for network analysis can be much larger than the number of measurements. For example, traffic engineering requires knowing the complete traffic matrix between all source and destination pairs, in order to properly configure traffic and avoid congestion. However, measuring the flow between all source and destination pairs is very expensive or even infeasible. Reconstructing data from a small number of measurements is an underconstrained problem. In addition, real-world data is complex and heterogeneous, and often violate the low-level assumptions required by existing compressive sensing techniques. These violations significantly reduce the applicability and effectiveness of existing compressive sensing methods. Third, synchronization of network data reduces the data ranks and increases spatial locality. However, periodic time series exhibit not only misalignment but also different frequencies, which makes it difficult to synchronize data in the time and frequency domains.The primary audience for this book is data engineers, analysts and researchers, who need to deal with big data with missing anomalous and synchronization problems. Advanced level students focused on compressive sensing techniques will also benefit from this book as a reference.

There is a need to keep track of advancements related to the network technologies and further investigate several research challenges to overcome for the ease of users. With this goal, the book provides most recent and prominent research works have been done related to the network technologies.

This book investigates the most advanced theories and methodologies of array beamforming, with a focus on antenna array enabled wireless communication technology.Combining with the current development needs and trends of wireless communication technology around the world, the authors explore the potentials and challenges of large-scale antenna array beamforming technology in next-generation mobile communication and some important emerging application scenarios. The book first introduces the basic structure of antenna array hierarchical codebook and channel estimation with high dimensionality, with which the time cost of searching the channel information can be effectively reduced. It then explicates high-efficiency beamforming transmission methods for point-to-point transmission, full-duplex point-to-point transmission, and point-to-multipoint transmission where array beamforming enabled non-orthogonal multiple access (NOMA) technologies for typical two-user systems and general multi-user systems are emphasized. The book also discusses array beamforming enabled unmanned aerial vehicle (UAV) communications and array beamforming enabled space/air/ground communications, with the uniqueness and relative solutions for single UAV systems and multi-UAV networks being analyzed.This will be a vital reference for researchers, students, and professionals interested in wireless communications, array beamforming, and millimeter-wave communications.

This book discusses 3D printing of sensors, actuators, and antennas and illustrates how manufacturers can create smart materials that can be effectively used to prepare low-cost products. The book also includes how to select the appropriate process for your manufacturing needs.

Master the fundamentals of digital communications systems with this accessible and hands-on introductory textbook, carefully interweaving theory and practice. The just-in-time approach introduces essential background as needed, keeping academic theory firmly linked to practical applications. The example-led teaching frames key concepts in the context of real-world systems, such as 5G, WiFi, and GPS. Stark provides foundational material on the trade-offs between energy and bandwidth efficiency, giving students a solid grounding in the fundamental challenges of designing digital communications systems. Features include over 300 illustrative figures, 80 examples, and 130 end-of-chapter problems to reinforce student understanding, with solutions for instructors. Accompanied online by lecture slides, computational MATLAB® and Python resources, and supporting data sets, this is the ideal introduction to digital communications for senior undergraduate and graduate students in electrical engineering.

In this report, researchers describe fifth-generation (5G) security and identify where the United States has security advantages or disadvantages relative to China in the 5G competition and how to preserve those advantages.

This book discusses the advancements in IoT and Cyber-Physical Systems Forensics. This book not only presents numerous case stories from a global perspective, but it also compiles a large amount of literature and research from a database.

This book covers advances and applications of smart technologies including the Internet of Things (IoT), artificial intelligence, and deep learning in areas such as manufacturing, production, renewable energy, and healthcare. It also covers wearable and implantable biomedical devices for healthcare monitoring, smart surveillance, and monitoring applications such as the use of an autonomous drone for disaster management and rescue operations. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the areas such as electrical engineering, electronics and communications engineering, computer engineering, and information technology. Covers concepts, theories, and applications of artificial intelligence and deep learning, from the perspective of the Internet of Things. Discusses powers predictive analysis, predictive maintenance, and automated processes for making manufacturing plants more efficient, profitable, and safe. Explores the importance of blockchain technology in the Internet of Things security issues. Discusses key deep learning concepts including trust management, identity management, security threats, access control, and privacy. Showcases the importance of intelligent algorithms for cloud-based Internet of Things applications.This text emphasizes the importance of innovation and improving the profitability of manufacturing plants using smart technologies such as artificial intelligence, deep learning, and the Internet of Things. It furtherdiscusses applications of smart technologies in diverse sectors such as agriculture, smart home, production, manufacturing, transport, and healthcare.

This book covers the inexorable exhaustion of the IPv4 address space, the interim fix to this based on Network Address Translation (NAT) and Private Addresses, and the differences between IPv4 and IPv6. It will help you understand the limitations and problems introduced by the use of NAT and introduce you to the far simpler network and software designs possible, using a larger, unified address space.IPv6, a mature and viable replacement for IPv4, is currently used by more than 36% of all global Internet traffic. Wireless telephone service providers in many countries have migrated their networks to IPv6 with great success. The elimination of NAT and Private Addresses has vastly simplified network design and implementation. Further, there are now enough public addresses allocated to accommodate all anticipated uses for the foreseeable future.Most networking products and software, especially open-source software, are already fully IPv6 compliant. Today, no business should purchase obsolete products that support only IPv4. The global IPv6 Forum estimates that there are millions of networking professionals still needing to learn the fundamentals of IPv6 technologies to move forward. This book is for them. With plans in place for a shutdown of IPv4 on global networks ("e;Sunset IPv4"e;) the time to learn is now. If you want a job in IT, especially network hardware or software, and you don't know IPv6, you are already obsolete.What You Will Learn This book serves as a guide to all relevant Internet Engineering Task Force (IETF) standards Request for Comments (RFCs), organized by topic and discussed in plain language Understand how IPv6 makes viable technologies such as multicast (for efficient global audio/video streaming), IPsec VPNs (for better security), and simpler VoIP Take "e;edge computing"e; to the limit by eliminating intermediary servers made necessary by IPv4 NAT-for example, making connections directly from my node to yours Discover how organizations can introduce IPv6 into existing IPv4 networks ("e;Dual Stack"e;), and then eliminate the legacy IPv4 aspects going forward ("e;Pure IPv6"e;) for the mandates going into place now (for example, US DoD requirements to move all networks to Pure IPv6)Recognize that 5G networking (the Grand Convergence of conventional networks and wireless service) depends heavily on the advanced features IPv6 Who This Book Is ForNetworking professionals. Readers should have at least some familiarity with the precursor protocol (IPv4) and legacy TCP/IP based networks. Some knowledge of network models, such as DoD four-layer model or OSI 7-layer model, is helpful to understand where the Internet Protocol fits into the larger picture. For network software developers using the Sockets API (in UNIX, Windows, etc.), this book will help you to understand the extensions to that API needed to work with IPv6.

This textbook presents computer networks to electrical and computer engineering students in a manner that is clearer, more interesting, and easier to understand than other texts.  All principles are presented in a lucid, logical, step-by-step manner. As much as possible, the authors avoid wordiness and giving too much detail that could hide concepts and impede overall understanding of the material. Ten review questions in the form of multiple-choice objective items are provided at the end of each chapter with answers. The review questions are intended to cover the little "e;tricks"e; which the examples and end-of-chapter problems may not cover. They serve as a self-test device and help students determine how well they have mastered the chapter.

The book examines the enhancement of the performance of fog networks for real-world applications using nature-based optimization techniques. It looks at the challenges in cloud datacenter nodes and fog computing networks and provides solutions. It covers such issues as security, privacy, and power consumption.

The Spatial Grasp Model suggests uses beyond the theoretical, including the examination of hurricanes and forest fires. Investigating group behaviour of ocean animals, discovery of unknown terrain features, and path-findings in large transport networks truly demonstrates the real-world application of SGL.

The concept of "smart city" is used widely in general however, it is hard to explain because of the complexity and multidimensionality of this notion. In this context, we aim to contribute literature with a value-added approach where different AI applications of smart cities are discussed from different perspective.

The concept of a "smart city" is used widely in general; however, it is hard to explain because of the complexity and multidimensionality of this notion. However, the essential qualification for being a smart city is to achieve "sustainable social, environmental, and economic development" and boost the living standards of society based on Information and Communication Technology (ICT) and Artificial intelligence (AI). AI in smart cities has become an important aspect for cities that face great challenges to make smart decisions for social well-being, particularly cybersecurity and corporate sustainability. In this context, we aim to contribute literature with a value-added approach where various AI applications of smart cities are discussed from a different perspective. First, we start by discussing the conceptual design, modeling, and determination of components for the sustainability of a smart city structure. Since smart cities operate on spatial-based data, it is important to design, operate, and manage smart city elements using Geographical Information Systems (GIS) technologies. Second, we define the structure, type, unit, and functionality of the layers to be placed on the GIS to achieve best practices based on Industry 4.0 components. Transportation is one of the key indicators of smart cities, so it is critical to make transportation in smart cities accessible for different disabled groups by using AI technologies. Third, we demonstrate what kinds of technologies should be used for which disabled groups in different transportation vehicles with specific examples. Finally, we create a discussion platform for processes and sub-processes such as waste management, emergency management, risk management, and data management for establishing smart cities including the financial and ethical aspects.

The book provides an overview of crude oil refining processes and presents a deep analysis of the current context and challenges in the downstream industry. It covers traditional refining processes, the impact of current trends, and technological routes available to help those in the industry survive in a highly competitive environment.

Focuses specifically on real-time applications in electronics, communications, computing, and information technology. Topics address applications for automotive use, detecting DoS attacks, social media and consumer applications, and hostel management, firefighting, and heart rate variability for predicting cardiac health.