About this book
Connections are important: in studying nature, technology, commerce and the social sciences, it often makes sense to focus on the pattern of interactions between individual components. Furthermore, improvements in computing power have made it possible to gather, store and analyze large data sets across many disciplines, and it is apparent that universal features may exist across seemingly disparate application areas.
Network Science is the emerging field concerned with the study of large, realistic networks. This interdisciplinary endeavor, focusing on the patterns of interactions that arise between individual components of natural and engineered systems, has been applied to data sets from activities as diverse as high-throughput biological experiments, online trading information, smart-meter utility supplies, and pervasive telecommunications and surveillance technologies.
This unique text/reference provides a fascinating insight into the state of the art in network science, highlighting the commonality across very different areas of application and the ways in which each area can be advanced by injecting ideas and techniques from another. The book includes contributions from an international selection of experts, providing viewpoints from a broad range of disciplines. It emphasizes networks that arise in nature - such as food webs, protein interactions, gene expression, and neural connections - and in technology - such as finance, airline transport, urban development and global trade.
Topics and Features:
- Begins with a clear overview chapter to introduce this interdisciplinary field
- Discusses the classic network science of fixed connectivity structures, including empirical studies, mathematical models and computational algorithms
- Examines time-dependent processes that take place over networks, covering topics such as synchronization, and message passing algorithms
- Investigates time-evolving networks, such as the World Wide Web and shifts in topological properties (connectivity, spectrum, percolation)
- Explores applications of complex networks in the physical and engineering sciences, looking ahead to new developments in the field
Researchers and professionals from disciplines as varied as computer science, mathematics, engineering, physics, chemistry, biology, ecology, neuroscience, epidemiology, and the social sciences will all benefit from this topical and broad overview of current activities and grand challenges in the unfolding field of network science.
Dr. Ernesto Estrada is a professor in the Department of Mathematics and Statistics, and the Department of Physics, at the University of Strathclyde, Glasgow, Scotland. Dr. Maria Fox is a professor and head of the Computer and Information Sciences Department at the University of Strathclyde. Dr. Des Higham is a professor in the Department of Mathematics and Statistics at the University of Strathclyde. Dr. Gian-Luca Oppo is a professor and chair of Computational and Nonlinear Physics in the Department of Physics at the University of Strathclyde.
Editors and affiliations
- Book Title Network Science
- Book Subtitle Complexity in Nature and Technology
Desmond J. Higham
- DOI https://doi.org/10.1007/978-1-84996-396-1
- Copyright Information Springer-Verlag London Limited 2010
- Publisher Name Springer, London
- eBook Packages Computer Science Computer Science (R0)
- Hardcover ISBN 978-1-84996-395-4
- Softcover ISBN 978-1-4471-6034-2
- eBook ISBN 978-1-84996-396-1
- Edition Number 1
- Number of Pages XI, 245
- Number of Illustrations 0 b/w illustrations, 0 illustrations in colour
Computer Communication Networks
Algorithm Analysis and Problem Complexity
Communications Engineering, Networks
Applications of Graph Theory and Complex Networks
- Buy this book on publisher's site
From the reviews:
“Unlike many existing books that address mathematical network science or that focus on a single application area, this book collects papers written by experts specializing in different fields. … the goal of this book is to broaden the view of readers. It focuses on applications of network science rather than on the mathematics of network analysis. It is suitable for readers with any background.” (Hsun-Hsien Chang, ACM Computing Reviews, March, 2011)