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\"This book offers the latest advances and results in the fields of Machine Learning and Deep Learning for Wireless Communication and provides positive and critical discussions on the challenges and prospects. It provides a broad spectrum in understanding the improvements in Machine Learning and Deep Learning that are motivating by the specific constraints posed by wireless networking systems. The book offers an extensive overview on intelligent Wireless Communication systems and its underlying technologies, research challenges, solutions, and case studies. It provides information on intelligent wireless communication systems and its models, algorithms and applications. The book is written as a reference that offers the latest technologies and research results to various industry problems\"-- Provided by publisher.

With the current explosion in network traffic, and mounting pressure on operators’ business case, Self-Organizing Networks (SON) play a crucial role. They are conceived to minimize human intervention in engineering processes and at the same time improve system performance to maximize Return-on-Investment (ROI) and secure customer loyalty. Written by leading experts in the planning and optimization of Multi-Technology and Multi-Vendor wireless networks, this book describes the architecture of Multi-Technology SON for GSM, UMTS and LTE, along with the enabling technologies for SON planning, optimization and healing. This is presented mainly from a technology point of view, but also covers some critical business aspects, such as the ROI of the proposed SON functionalities and Use Cases. Key features: Follows a truly Multi-Technology approach: covering not only LTE, but also GSM and UMTS, including architectural considerations of deploying SON in today’s GSM and UMTS networks Features detailed discussions about the relevant trade-offs in each Use Case Includes field results of today’s GSM and UMTS SON implementations in live networks Addresses the calculation of ROI for Multi-Technology SON, contributing to a more complete and strategic view of the SON paradigm This book will appeal to network planners, optimization engineers, technical/strategy managers with operators and R&D/system engineers at infrastructure and software vendors. It will also be a useful resource for postgraduate students and researchers in automated wireless network planning and optimization.

Systematically introduces self-healing control theory for distribution networks, rigorously supported by simulations and applications • A comprehensive introduction to self-healing control for distribution networks • Details the construction of self-healing control systems with simulations and applications • Provides key principles for new generation protective relay and network protection • Demonstrates how to monitor and manage system performance • Highlights practical implementation of self-healing control technologies, backed by rigorous research data and simulations

Software Defined Networking simplifies design, monitoring and management of next generation networks by segregating a legacy network into a centralized control plane and a remotely programmable data plane. The intelligent centralized SDN control plane controls behavior of forwarding devices in processing the incoming packets and provides a bird-eye view of entire network at a single central point. The centralized control provides network programmability and facilitates introduction of adaptive and automatic network control. The SDN control plane can be implemented by using following three deployment models: (i) physically centralized, in which a single SDN controller is configured for a network; (ii) physically distributed but logically centralized, wherein multiple SDN controllers are used to manage a network; and (iii) hybrid, in which both legacy distributed control and centralized SDN control coexist. This manuscript presents all these control plane architectures and discusses various SDN controllers supporting these architectures. We have analyzed more than forty SDN controllers in terms of following performance parameters: scalability, reliability, consistency and security. We have examined the mechanisms used by various SDN controllers to address the said performance parameters and have highlighted the pros and cons associated with each mechanism. In addition to it, this manuscript also highlights number of research challenges and open issues in different SDN control plane architectures.

Communication between vehicles and infrastructure will enable an entirely new way of managing and accommodating traffic, pedestrians, and the surrounding environment, changing the nature of travel going forward. Networking Vehicles to Everything provides those seriously interested in vehicular automation with a state of the art resource for a deep understanding of the many competing technologies that will be united to enable the technology in years to come. This in-depth account covers challenges, case considerations, current activities in standards, product implementation, and upcoming trends such as software reconfiguration, mmWave technology and advanced control theory tools. Readers will gain in-depth understanding of the main bodies and institutions developing and regulating the technology, current technological battles including in particular IEEE 802.11p and 3GPP LTE V2X technologies which compete for the top-spot in a multi-billion market. Readers will become aware of the many currently open technological questions and trends in terms of applications, markets and some of the possibilities that the future may hold for any type of vehicle.

Vehicular Ad-hoc network (VANET) is an imminent technology having both exciting prospects and substantial challenges, especially in terms of security. Due to its distributed network and frequently changing topology, it is extremely prone to security attacks. The researchers have proposed different strategies for detecting various forms of network attacks. However, VANET is still exposed to several attacks, specifically Sybil attack. Sybil Attack is one of the most challenging attacks in VANETS, which forge false identities in the network to undermine communication between network nodes. This attack highly impacts transportation safety services and may create traffic congestion. In this regard, a novel collaborative framework based on majority voting is proposed to detect the Sybil attack in the network. The framework works by ensembling individual classifiers, i.e., K-Nearest Neighbor, Naïve Bayes, Decision Tree, SVM, and Logistic Regression in a parallel manner. The Majority Voting (Hard and Soft) mechanism is adopted for a final prediction. A comparison is made between Majority Voting Hard and soft to choose the best approach. With the proposed approach, 95% accuracy is achieved. The proposed framework is also evaluated using the Receiver operating characteristics curve (ROC-curve).

With the accelerating process of world industrialization, countries pay more attention to industrial modernization. In order to solve the problems of traditional control technology and system with low accuracy, high energy consumption, and high delay in industrial automation control and the difficulty in adapting to the new industrial production process, the new industrial automation control system is discussed and studied. The industrial automation control is studied, and a new monitoring system is designed for automation control by using ZigBee wireless communication technology. The design of the system data communication scheme is completed by the in-depth study and summary of ZigBee wireless communication technology. The hardware structure and software structure of ZigBee wireless communication module are designed, and the wireless monitoring system using ZigBee is established. Taking the production workshop of a pharmaceutical factory as the monitoring object, the working stability and data transmission efficiency of the model are tested. The experiment shows that the ZigBee wireless transmission model has lower temperature and better stability than the wired transmission system in the working process. Compared with the traditional wired control system, the temperature of ZigBee wireless control system is lower when it works. The difference between the highest temperature and the lowest temperature is 0.1°C. In the overall work flow, the system temperature is lower than that of the wired control. ZigBee wireless control has good stability. Subsequently, the method of manually setting obstacles is used to test the effectiveness of data transmission. The experiment found that in the absence of barrier, the maximum effective transmission distance was 40 meters, and the packet loss rate was very low, which could ensure the timeliness of data. Therefore, this system can be applied to industrial automation control. The research results can provide some reference for the design of new control systems in other industrial control fields. The improved system can also be applied to other industries. ZigBee is a short-range technology for wireless sensor networks, and it is a two-way communication technology with low power consumption, low data rate, and low cost. It can be applied to automatic control and remote control. This provides a platform for wireless networking and control of small and cheap devices. ZigBee will not compete with connection technologies such as Wi-Fi. Meanwhile, it will greatly stimulate the progress of the industrial market.

Over the years, the number of vehicles has increased dramatically, which has led to serious problems such as traffic jams, accidents, and many other problems, as cities turn into smart cities. In recent years, traffic jams have become one of the main challenges for engineers and designers to create an intelligent traffic management system capable of effectively detecting and reducing the overall density of traffic in most urban areas visited by motorists such as offices, downtown, and establishments based on several modern technologies, including wireless sensor networks (WSNs), surveillance camera, and IoT. In this article, we propose an intelligent traffic control system based on the design of a wireless sensor network (WSN) in order to collect data on road traffic and also on available parking spaces in a smart city. In addition, the proposed system has innovative services that allow drivers to view the traffic rate and the number of available parking spaces to their destination remotely using an Android mobile application to avoid traffic jams and to take another alternative route to avoid getting stuck and also to make it easier for drivers when looking for a free parking space to avoid unnecessary trips. Our system integrates three smart subsystems connected to each other (crossroad management, parking space management, and a mobile application) in order to connect citizens to a smart city.