Distributed Data Fusion for Network-Centric Operations
Distributed Data Fusion for Network-Centric Operations

Author: David Hall

Publisher: CRC Press

Published: 2017-12-19

Total Pages: 501

ISBN-13: 1351833057

DOWNLOAD EBOOK

With the recent proliferation of service-oriented architectures (SOA), cloud computing technologies, and distributed-interconnected systems, distributed fusion is taking on a larger role in a variety of applications—from environmental monitoring and crisis management to intelligent buildings and defense. Drawing on the work of leading experts around the world, Distributed Data Fusion for Network-Centric Operations examines the state of the art of data fusion in a distributed sensing, communications, and computing environment. Get Insight into Designing and Implementing Data Fusion in a Distributed Network Addressing the entirety of information fusion, the contributors cover everything from signal and image processing, through estimation, to situation awareness. In particular, the work offers a timely look at the issues and solutions involving fusion within a distributed network enterprise. These include critical design problems, such as how to maintain a pedigree of agents or nodes that receive information, provide their contribution to the dataset, and pass to other network components. The book also tackles dynamic data sharing within a network-centric enterprise, distributed fusion effects on state estimation, graph-theoretic methods to optimize fusion performance, human engineering factors, and computer ontologies for higher levels of situation assessment. A comprehensive introduction to this emerging field and its challenges, the book explores how data fusion can be used within grid, distributed, and cloud computing architectures. Bringing together both theoretical and applied research perspectives, this is a valuable reference for fusion researchers and practitioners. It offers guidance and insight for those working on the complex issues of designing and implementing distributed, decentralized information fusion.

Distributed Data Fusion for Network-centric Operations
Distributed Data Fusion for Network-centric Operations

Author: David Lee Hall

Publisher:

Published: 2013

Total Pages: 478

ISBN-13: 9781351824361

DOWNLOAD EBOOK

"Foreword I am very pleased to provide a foreword for this timely work on distributed fusion. I have been involved in fusion research for the last 15 years, focused on transforming data to support more effective decision making. During that time, I have relied heavily on the advice of the editors of this book and many of the chapter authors to help set the directions for Army-focused basic and applied information fusion initiatives. I first met the editors about 12 years ago at an Army-sponsored fusion workshop where it was clear that the issues of increased sensors and data sources, along with the introduction of web-based information architectures, had finally overwhelmed the analysis community. Most of the discussions were focused on the problems. But Dave Hall and Jim Llinas began addressing the solutions. They identified relevant terms and definitions, outlined algorithms for specific fusion tasks, addressed many of the evolving architectural issues, pinpointed key technical barriers, and proposed directions for future research. They clearly were long-time experts in the field; but, more importantly, they were visionary in their recognition of rapidly evolving trends in information management and the impact those trends would have on the field of data fusion. It is, therefore, not at all surprising that this, their latest book (along with colleagues), would be focused on distributed fusion. While there are numerous texts and handbooks on data fusion in general (many written or edited by the editors and authors of this book), there are two major trends that motivate the need for this work. First, the very concept of defense operations has dramatically changed. Modern military missions include, for example, coalitionbased counterinsurgency, counternarcotics, "--

Multisensor Data Fusion
Multisensor Data Fusion

Author: David Hall

Publisher: CRC Press

Published: 2001-06-20

Total Pages: 564

ISBN-13: 1420038540

DOWNLOAD EBOOK

The emerging technology of multisensor data fusion has a wide range of applications, both in Department of Defense (DoD) areas and in the civilian arena. The techniques of multisensor data fusion draw from an equally broad range of disciplines, including artificial intelligence, pattern recognition, and statistical estimation. With the rapid evolut

Distributed Sensor Networks
Distributed Sensor Networks

Author: S. Sitharama Iyengar

Publisher: CRC Press

Published: 2016-04-19

Total Pages: 927

ISBN-13: 1439862885

DOWNLOAD EBOOK

The best-selling Distributed Sensor Networks became the definitive guide to understanding this far-reaching technology. Preserving the excellence and accessibility of its predecessor, Distributed Sensor Networks, Second Edition once again provides all the fundamentals and applications in one complete, self-contained source. Ideal as a tutorial for

Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications
Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications

Author: Arthur A. Andraitis

Publisher: SPIE-International Society for Optical Engineering

Published: 2004

Total Pages: 214

ISBN-13: 9780819453327

DOWNLOAD EBOOK

Proceedings of SPIE present the original research papers presented at SPIE conferences and other high-quality conferences in the broad-ranging fields of optics and photonics. These books provide prompt access to the latest innovations in research and technology in their respective fields. Proceedings of SPIE are among the most cited references in patent literature.

Data Fusion and Data Mining for Power System Monitoring
Data Fusion and Data Mining for Power System Monitoring

Author: Arturo Román Messina

Publisher: CRC Press

Published: 2020-05-05

Total Pages: 267

ISBN-13: 1000065898

DOWNLOAD EBOOK

Data Fusion and Data Mining for Power System Monitoring provides a comprehensive treatment of advanced data fusion and data mining techniques for power system monitoring with focus on use of synchronized phasor networks. Relevant statistical data mining techniques are given, and efficient methods to cluster and visualize data collected from multiple sensors are discussed. Both linear and nonlinear data-driven mining and fusion techniques are reviewed, with emphasis on the analysis and visualization of massive distributed data sets. Challenges involved in realistic monitoring, visualization, and analysis of observation data from actual events are also emphasized, supported by examples of relevant applications. Features Focuses on systematic illustration of data mining and fusion in power systems Covers issues of standards used in the power industry for data mining and data analytics Applications to a wide range of power networks are provided including distribution and transmission networks Provides holistic approach to the problem of data mining and data fusion using cutting-edge methodologies and technologies Includes applications to massive spatiotemporal data from simulations and actual events

Distributed and Cloud Computing
Distributed and Cloud Computing

Author: Kai Hwang

Publisher: Morgan Kaufmann

Published: 2013-12-18

Total Pages: 671

ISBN-13: 0128002042

DOWNLOAD EBOOK

Distributed and Cloud Computing: From Parallel Processing to the Internet of Things offers complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing. It is the first modern, up-to-date distributed systems textbook; it explains how to create high-performance, scalable, reliable systems, exposing the design principles, architecture, and innovative applications of parallel, distributed, and cloud computing systems. Topics covered by this book include: facilitating management, debugging, migration, and disaster recovery through virtualization; clustered systems for research or ecommerce applications; designing systems as web services; and social networking systems using peer-to-peer computing. The principles of cloud computing are discussed using examples from open-source and commercial applications, along with case studies from the leading distributed computing vendors such as Amazon, Microsoft, and Google. Each chapter includes exercises and further reading, with lecture slides and more available online. This book will be ideal for students taking a distributed systems or distributed computing class, as well as for professional system designers and engineers looking for a reference to the latest distributed technologies including cloud, P2P and grid computing. - Complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing - Includes case studies from the leading distributed computing vendors: Amazon, Microsoft, Google, and more - Explains how to use virtualization to facilitate management, debugging, migration, and disaster recovery - Designed for undergraduate or graduate students taking a distributed systems course—each chapter includes exercises and further reading, with lecture slides and more available online

Statistical Multisource-multitarget Information Fusion
Statistical Multisource-multitarget Information Fusion

Author: Ronald P. S. Mahler

Publisher: Artech House Publishers

Published: 2007

Total Pages: 892

ISBN-13:

DOWNLOAD EBOOK

This comprehensive resource provides you with an in-depth understanding of finite-set statistics (FISST) ndash; a recently developed method which unifies much of information fusion under a single probabilistic, in fact Bayesian, paradigm. The book helps you master FISST concepts, techniques, and algorithms, so you can use FISST to address real-world challenges in the field. You learn how to model, fuse, and process highly disparate information sources, and detect and track non-cooperative individual/platform groups and conventional non-cooperative targets.