Capacity Analysis of Vehicular Communication Networks

Capacity Analysis of Vehicular Communication Networks PDF Author: Ning Lu
Publisher: Springer Science & Business Media
ISBN: 1461483972
Category : Computers
Languages : en
Pages : 91

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Book Description
This SpringerBrief focuses on the network capacity analysis of VANETs, a key topic as fundamental guidance on design and deployment of VANETs is very limited. Moreover, unique characteristics of VANETs impose distinguished challenges on such an investigation. This SpringerBrief first introduces capacity scaling laws for wireless networks and briefly reviews the prior arts in deriving the capacity of VANETs. It then studies the unicast capacity considering the socialized mobility model of VANETs. With vehicles communicating based on a two-hop relaying scheme, the unicast capacity bound is derived and can be applied to predict the throughput of real-world scenarios of VANETs. The downlink capacity of VANETs is also investigated in which access infrastructure is deployed to provide pervasive Internet access to vehicles. Different alternatives of wireless access infrastructure are considered. A lower bound of downlink capacity is derived for each type of access infrastructure. The last section of this book presents a case study based on a perfect city grid to examine the capacity-cost trade-offs of different deployments since the deployment costs of different access infrastructure are highly variable.

Capacity Analysis of Vehicular Communication Networks

Capacity Analysis of Vehicular Communication Networks PDF Author: Ning Lu
Publisher: Springer Science & Business Media
ISBN: 1461483972
Category : Computers
Languages : en
Pages : 91

Get Book Here

Book Description
This SpringerBrief focuses on the network capacity analysis of VANETs, a key topic as fundamental guidance on design and deployment of VANETs is very limited. Moreover, unique characteristics of VANETs impose distinguished challenges on such an investigation. This SpringerBrief first introduces capacity scaling laws for wireless networks and briefly reviews the prior arts in deriving the capacity of VANETs. It then studies the unicast capacity considering the socialized mobility model of VANETs. With vehicles communicating based on a two-hop relaying scheme, the unicast capacity bound is derived and can be applied to predict the throughput of real-world scenarios of VANETs. The downlink capacity of VANETs is also investigated in which access infrastructure is deployed to provide pervasive Internet access to vehicles. Different alternatives of wireless access infrastructure are considered. A lower bound of downlink capacity is derived for each type of access infrastructure. The last section of this book presents a case study based on a perfect city grid to examine the capacity-cost trade-offs of different deployments since the deployment costs of different access infrastructure are highly variable.

LTE-Advanced and Next Generation Wireless Networks

LTE-Advanced and Next Generation Wireless Networks PDF Author: Guillaume de la Roche
Publisher: John Wiley & Sons
ISBN: 1118411013
Category : Technology & Engineering
Languages : en
Pages : 552

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Book Description
LTE- A and Next Generation Wireless Networks: Channel Modeling and Performance describes recent advances in propagation and channel modeling necessary for simulating next generation wireless systems. Due to the radio spectrum scarcity, two fundamental changes are anticipated compared to the current status. Firstly, the strict reservation of a specific band for a unique standard could evolve toward a priority policy allowing the co-existence of secondary users in a band allocated to a primary system. Secondly, a huge increase of the number of cells is expected by combining outdoor base stations with smaller cells such as pico/femto cells and relays. This evolution is accompanied with the emergence of cognitive radio that becomes a reality in terminals together with the development of self-organization capabilities and distributed cooperative behaviors. The book is divided into three parts: Part I addresses the fundamentals (e.g. technologies, channel modeling principles etc.) Part II addresses propagation and modeling discussing topics such as indoor propagation, outdoor propagation, etc. Part III explores system performance and applications (e.g. MIMO Over-the-air testing, electromagnetic safety, etc).

Inter-Vehicle Communication at Intersections

Inter-Vehicle Communication at Intersections PDF Author: Thomas Mangel
Publisher: KIT Scientific Publishing
ISBN: 3866448996
Category : Computers
Languages : en
Pages : 212

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Book Description
This book evaluates the ability of ad-hoc and cellular communication to enable cross-traffic assistance at intersections. Potential issues like Non-Line-Of-Sight (NLOS) reception with ad-hoc and limited capacity, higher latency and costs with cellular technology are investigated in two individual evaluations. A method for efficient information delivery via cellular systems and an inter-vehicle NLOS radio propagation model are proposed. Finally, the suitability of both technologies is compared.

Visible Light Communication

Visible Light Communication PDF Author: Suseela Vappangi
Publisher: CRC Press
ISBN: 1000416208
Category : Technology & Engineering
Languages : en
Pages : 503

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Book Description
The field of visible light communication (VLC) has diverse applications to the end user including streaming audio, video, high-speed data browsing, voice over internet and online gaming. This comprehensive textbook discusses fundamental aspects, research activities and modulation techniques in the field of VLC. Visible Light Communication: A Comprehensive Theory and Applications with MATLAB® discusses topics including line of sight (LOS) propagation model, non-line of sight (NLOS) propagation model, carrier less amplitude and phase modulation, multiple-input-multiple-output (MIMO), non-linearities of optical sources, orthogonal frequency-division multiple access, non-orthogonal multiple access and single-carrier frequency-division multiple access in depth. Primarily written for senior undergraduate and graduate students in the field of electronics and communication engineering for courses on optical wireless communication and VLC, this book: Provides up-to-date literature in the field of VLC Presents MATLAB codes and simulations to help readers understand simulations Discusses applications of VLC in enabling vehicle to vehicle (V2V) communication Covers topics including radio frequency (RF) based wireless communications and VLC Presents modulation formats along with the derivations of probability of error expressions pertaining to different variants of optical OFDM

Network Traffic Engineering

Network Traffic Engineering PDF Author: Andrea Baiocchi
Publisher: John Wiley & Sons
ISBN: 1119632439
Category : Technology & Engineering
Languages : en
Pages : 816

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Book Description
A comprehensive guide to the concepts and applications of queuing theory and traffic theory Network Traffic Engineering: Models and Applications provides an advanced level queuing theory guide for students with a strong mathematical background who are interested in analytic modeling and performance assessment of communication networks. The text begins with the basics of queueing theory before moving on to more advanced levels. The topics covered in the book are derived from the most cutting-edge research, project development, teaching activity, and discussions on the subject. They include applications of queuing and traffic theory in: LTE networks Wi-Fi networks Ad-hoc networks Automated vehicles Congestion control on the Internet The distinguished author seeks to show how insight into practical and real-world problems can be gained by means of quantitative modeling. Perfect for graduate students of computer engineering, computer science, telecommunication engineering, and electrical engineering, Network Traffic Engineering offers a supremely practical approach to a rapidly developing field of study and industry.

Numerical Optimization in Engineering and Sciences

Numerical Optimization in Engineering and Sciences PDF Author: Debashis Dutta
Publisher: Springer Nature
ISBN: 981153215X
Category : Technology & Engineering
Languages : en
Pages : 569

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Book Description
This book presents select peer-reviewed papers presented at the International Conference on Numerical Optimization in Engineering and Sciences (NOIEAS) 2019. The book covers a wide variety of numerical optimization techniques across all major engineering disciplines like mechanical, manufacturing, civil, electrical, chemical, computer, and electronics engineering. The major focus is on innovative ideas, current methods and latest results involving advanced optimization techniques. The contents provide a good balance between numerical models and analytical results obtained for different engineering problems and challenges. This book will be useful for students, researchers, and professionals interested in engineering optimization techniques.

Wireless Technologies in Vehicular Ad Hoc Networks: Present and Future Challenges

Wireless Technologies in Vehicular Ad Hoc Networks: Present and Future Challenges PDF Author: Aquino-Santos, Raul
Publisher: IGI Global
ISBN: 1466602104
Category : Computers
Languages : en
Pages : 383

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Book Description
"This book explores different models for inter-vehicular communication, in which vehicles are equipped with on-board computers that function as nodes in a wireless network"--Provided by publisher.

Simulation Tools and Techniques

Simulation Tools and Techniques PDF Author: Houbing Song
Publisher: Springer Nature
ISBN: 3030727955
Category : Mathematics
Languages : en
Pages : 780

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Book Description
This two-volume set constitutes the refereed post-conference proceedings of the 12th International Conference on Simulation Tools and Techniques, SIMUTools 2020, held in Guiyang, China, in August 2020. Due to COVID-19 pandemic the conference was held virtually. The 125 revised full papers were carefully selected from 354 submissions. The papers focus on simulation methods, simulation techniques, simulation software, simulation performance, modeling formalisms, simulation verification and widely used frameworks.

Opportunistic Spectrum Utilization in Vehicular Communication Networks

Opportunistic Spectrum Utilization in Vehicular Communication Networks PDF Author: Nan Cheng
Publisher: Springer
ISBN: 3319204459
Category : Technology & Engineering
Languages : en
Pages : 82

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Book Description
This brief examines current research on improving Vehicular Networks (VANETs), examining spectrum scarcity due to the dramatic growth of mobile data traffic and the limited bandwidth of dedicated vehicular communication bands and the use of opportunistic spectrum bands to mitigate congestion. It reviews existing literature on the use of opportunistic spectrum bands for VANETs, including licensed and unlicensed spectrum bands and a variety of related technologies, such as cognitive radio, WiFi and device-to-device communications. Focused on analyzing spectrum characteristics, designing efficient spectrum exploitation schemes, and evaluating the date delivery performance when utilizing different opportunistic spectrum bands, the results presented in this brief provide valuable insights on improving the design and deployment of future VANETs.

Applications

Applications PDF Author: Katharina Morik
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110785986
Category : Science
Languages : en
Pages : 478

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Book Description
Machine learning is part of Artificial Intelligence since its beginning. Certainly, not learning would only allow the perfect being to show intelligent behavior. All others, be it humans or machines, need to learn in order to enhance their capabilities. In the eighties of the last century, learning from examples and modeling human learning strategies have been investigated in concert. The formal statistical basis of many learning methods has been put forward later on and is still an integral part of machine learning. Neural networks have always been in the toolbox of methods. Integrating all the pre-processing, exploitation of kernel functions, and transformation steps of a machine learning process into the architecture of a deep neural network increased the performance of this model type considerably. Modern machine learning is challenged on the one hand by the amount of data and on the other hand by the demand of real-time inference. This leads to an interest in computing architectures and modern processors. For a long time, the machine learning research could take the von-Neumann architecture for granted. All algorithms were designed for the classical CPU. Issues of implementation on a particular architecture have been ignored. This is no longer possible. The time for independently investigating machine learning and computational architecture is over. Computing architecture has experienced a similarly rampant development from mainframe or personal computers in the last century to now very large compute clusters on the one hand and ubiquitous computing of embedded systems in the Internet of Things on the other hand. Cyber-physical systems’ sensors produce a huge amount of streaming data which need to be stored and analyzed. Their actuators need to react in real-time. This clearly establishes a close connection with machine learning. Cyber-physical systems and systems in the Internet of Things consist of diverse components, heterogeneous both in hard- and software. Modern multi-core systems, graphic processors, memory technologies and hardware-software codesign offer opportunities for better implementations of machine learning models. Machine learning and embedded systems together now form a field of research which tackles leading edge problems in machine learning, algorithm engineering, and embedded systems. Machine learning today needs to make the resource demands of learning and inference meet the resource constraints of used computer architecture and platforms. A large variety of algorithms for the same learning method and, moreover, diverse implementations of an algorithm for particular computing architectures optimize learning with respect to resource efficiency while keeping some guarantees of accuracy. The trade-off between a decreased energy consumption and an increased error rate, to just give an example, needs to be theoretically shown for training a model and the model inference. Pruning and quantization are ways of reducing the resource requirements by either compressing or approximating the model. In addition to memory and energy consumption, timeliness is an important issue, since many embedded systems are integrated into large products that interact with the physical world. If the results are delivered too late, they may have become useless. As a result, real-time guarantees are needed for such systems. To efficiently utilize the available resources, e.g., processing power, memory, and accelerators, with respect to response time, energy consumption, and power dissipation, different scheduling algorithms and resource management strategies need to be developed. This book series addresses machine learning under resource constraints as well as the application of the described methods in various domains of science and engineering. Turning big data into smart data requires many steps of data analysis: methods for extracting and selecting features, filtering and cleaning the data, joining heterogeneous sources, aggregating the data, and learning predictions need to scale up. The algorithms are challenged on the one hand by high-throughput data, gigantic data sets like in astrophysics, on the other hand by high dimensions like in genetic data. Resource constraints are given by the relation between the demands for processing the data and the capacity of the computing machinery. The resources are runtime, memory, communication, and energy. Novel machine learning algorithms are optimized with regard to minimal resource consumption. Moreover, learned predictions are applied to program executions in order to save resources. The three books will have the following subtopics: Volume 1: Machine Learning under Resource Constraints - Fundamentals Volume 2: Machine Learning and Physics under Resource Constraints - Discovery Volume 3: Machine Learning under Resource Constraints - Applications Volume 3 describes how the resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples. In the areas of health and medicine, it is demonstrated how machine learning can improve risk modelling, diagnosis, and treatment selection for diseases. Machine learning supported quality control during the manufacturing process in a factory allows to reduce material and energy cost and save testing times is shown by the diverse real-time applications in electronics and steel production as well as milling. Additional application examples show, how machine-learning can make traffic, logistics and smart cities more efficient and sustainable. Finally, mobile communications can benefit substantially from machine learning, for example by uncovering hidden characteristics of the wireless channel.