The Effects Of Traffic Structure On Application And Network Performance
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The Effects of Traffic Structure on Application and Network Performance
Author: Jay Aikat
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-12
Over the past three decades, the Internet's rapid growth has spurred the development of new applications in mobile computing, digital music, online video, gaming and social networks. These applications rely heavily upon various underlying network protocols and mechanisms to enable, maintain and enhance their Internet functionality The Effects of Traffic Structure on Application and Network Performance provides the necessary tools for maximizing the network efficiency of any Internet application, and presents ground-breaking research that will influence how these applications are built in the future. The book outlines how to design and run all types of networking experiments, and establishes the best practices in synthetic traffic generation for current and future researchers and practitioners to follow. It addresses some basic concepts and methods of traffic generation, but also details extensive empirical research in testing and evaluating network protocols and applications within a laboratory setting. The Effects of Traffic Structure on Application and Network Performance is designed as a reference book for networking professionals who must design, plan, test and evaluate their networks. Advanced-level students and researchers in computer science and engineering will find this book valuable as well
Advances and Applications in SmartRail, Traffic, and Transportation Engineering
This book is a collection of the original peer-reviewed conference papers presented at the 2024 2nd International Conference on SmartRail, Traffic, and Transportation Engineering, organized by Chongqing Jiaotong University and Southwest Jiaotong University. The conference will be held on 25-27 October 2024 in Chongqing, China. It covers topics including SmartRail systems, autonomous vehicles, energy efficiency, sustainable transportation, big data in transportation, and machine learning. Speakers discussed innovative technologies and strategies to improve the efficiency, reliability, and safety of rail networks while exploring the opportunities and challenges of integrating autonomous vehicles into existing transportation networks. It provides valuable insights into the latest developments and trends in transportation engineering and technology, with a focus on electrification and sustainable transportation. It serves as a valuable resource for professionals, researchers, and students working in the field.
ITS Sensors and Architectures for Traffic Management and Connected Vehicles
An intelligent transportation system (ITS) offers considerable opportunities for increasing the safety, efficiency, and predictability of traffic flow and reducing vehicle emissions. Sensors (or detectors) enable the effective gathering of arterial and controlled-access highway information in support of automatic incident detection, active transportation and demand management, traffic-adaptive signal control, and ramp and freeway metering and dispatching of emergency response providers. As traffic flow sensors are integrated with big data sources such as connected and cooperative vehicles, and cell phones and other Bluetooth-enabled devices, more accurate and timely traffic flow information can be obtained. The book examines the roles of traffic management centers that serve cities, counties, and other regions, and the collocation issues that ensue when multiple agencies share the same space. It describes sensor applications and data requirements for several ITS strategies; sensor technologies; sensor installation, initialization, and field-testing procedures; and alternate sources of traffic flow data. The book addresses concerns related to the introduction of automated and connected vehicles, and the benefits that systems engineering and national ITS architectures in the US, Europe, Japan, and elsewhere bring to ITS. Sensor and data fusion benefits to traffic management are described, while the Bayesian and Dempster–Shafer approaches to data fusion are discussed in more detail. ITS Sensors and Architectures for Traffic Management and Connected Vehicles suits the needs of personnel in transportation institutes and highway agencies, and students in undergraduate or graduate transportation engineering courses.