Large-Scale Simulation
Models, Algorithms, and Applications
Published on 19. December 2017
259 pages
978-1-4398-6896-6 (ISBN)
Description
Large-Scale Simulation: Models, Algorithms, and Applications gives you firsthand insight on the latest advances in large-scale simulation techniques. Most of the research results are drawn from the authors' papers in top-tier, peer-reviewed, scientific conference proceedings and journals.
The first part of the book presents the fundamentals of large-scale simulation, including high-level architecture and runtime infrastructure. The second part covers middleware and software architecture for large-scale simulations, such as decoupled federate architecture, fault tolerant mechanisms, grid-enabled simulation, and federation communities. In the third part, the authors explore mechanisms-such as simulation cloning methods and algorithms-that support quick evaluation of alternative scenarios. The final part describes how distributed computing technologies and many-core architecture are used to study social phenomena.
Reflecting the latest research in the field, this book guides you in using and further researching advanced models and algorithms for large-scale distributed simulation. These simulation tools will help you gain insight into large-scale systems across many disciplines.
The first part of the book presents the fundamentals of large-scale simulation, including high-level architecture and runtime infrastructure. The second part covers middleware and software architecture for large-scale simulations, such as decoupled federate architecture, fault tolerant mechanisms, grid-enabled simulation, and federation communities. In the third part, the authors explore mechanisms-such as simulation cloning methods and algorithms-that support quick evaluation of alternative scenarios. The final part describes how distributed computing technologies and many-core architecture are used to study social phenomena.
Reflecting the latest research in the field, this book guides you in using and further researching advanced models and algorithms for large-scale distributed simulation. These simulation tools will help you gain insight into large-scale systems across many disciplines.
More details
Language
English
Place of publication
Baton Rouge
United States
Publishing group
Taylor & Francis Inc
Target group
College/higher education
Students of distributed and parallel computing, and simulation. Postgraduate computer science students. Software developers and IT professionals.
Illustrations
107 s/w Abbildungen, 18 s/w Tabellen
18 Tables, black and white; 107 Illustrations, black and white
File size
5,10 MB
ISBN-13
978-1-4398-6896-6 (9781439868966)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Book
03/2017
1st Edition
CRC Press
€122.90
Shipment within 10-20 days
Book
05/2012
1st Edition
CRC Press
€299.50
Shipment within 15-20 days
Persons
Dan Chen is a professor and director of the Scientific Computing Lab at the China University of Geosciences. His research interests include computer-based modeling and simulation, high performance computing, and neuroinformatics.
Lizhe Wang is a professor at the Center for Earth Observation and Digital Earth, Chinese Academy of Sciences. Dr. Wang is also a "ChuTian Scholar" Chair Professor at the China University of Geosciences, a senior member of IEEE, and a member of ACM. His research interests include high performance computing, grid/cloud computing, and data-intensive computing.
Jingying Chen is a professor in the National Engineering Centre for e-Learning at Huazhong Normal University. Her research interests include intelligent systems, computer vision, and pattern recognition.
Lizhe Wang is a professor at the Center for Earth Observation and Digital Earth, Chinese Academy of Sciences. Dr. Wang is also a "ChuTian Scholar" Chair Professor at the China University of Geosciences, a senior member of IEEE, and a member of ACM. His research interests include high performance computing, grid/cloud computing, and data-intensive computing.
Jingying Chen is a professor in the National Engineering Centre for e-Learning at Huazhong Normal University. Her research interests include intelligent systems, computer vision, and pattern recognition.
Content
FUNDAMENTALS: Introduction. Background and Fundamentals. MIDDLEWARE AND SOFTWARE ARCHITECTURES: A Decoupled Federate Architecture. Fault-Tolerant HLA-Based Distributed Simulations. Synchronization in Federation Community Networks. EVALUATION OF ALTERNATIVE SCENARIOS: Theory and Issues in Distributed Simulation Cloning. Alternative Solutions for Cloning in HLA-Based Distributed Simulation. Managing Scenarios. Algorithms for Distributed Simulation Cloning. Experiments and Results of Simulation Cloning Algorithms. APPLICATIONS: Hybrid Modeling and Simulation of a Huge Crowd over an HGA. Massively Parallel M&S of a Large Crowd with GPGPU. Index.
