Advanced Methods for Complex Network Analysis

Advanced Methods for Complex Network Analysis

Release Date: April, 2016|Copyright: © 2016 |Pages: 461
DOI: 10.4018/978-1-4666-9964-9
ISBN13: 9781466699649|ISBN10: 1466699647|EISBN13: 9781466699656
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Description & Coverage
Description:

As network science and technology continues to gain popularity, it becomes imperative to develop procedures to examine emergent network domains, as well as classical networks, to help ensure their overall optimization.

Advanced Methods for Complex Network Analysis features the latest research on the algorithms and analysis measures being employed in the field of network science. Highlighting the application of graph models, advanced computation, and analytical procedures, this publication is a pivotal resource for students, faculty, industry practitioners, and business professionals interested in theoretical concepts and current developments in network domains.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Autonomous System Networks
  • Distributed Systems
  • Evolutionary Computation
  • Network Architecture
  • Social Network Analysis
  • Virus Propagation
  • Wireless Networks
Reviews & Statements

This work gathers international contributors in computer science, information systems, telecommunication engineering, and information technology to present the latest research in complex network analysis and applications in various areas, including medicine and academic programming. Coverage encompasses current graph models, algorithms, analysis measures, and tools for network science research and practice. The book contains b&w charts, graphs, and images throughout. With standalone tutorial-style chapters, the book is appropriate for students and researchers in network science as well as industry practitioners and business professionals.

– ProtoView Reviews
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Editor/Author Biographies
Natarajan Meghanathan is a tenured Full Professor of Computer Science at Jackson State University, Jackson, MS. He graduated with a Ph.D. in Computer Science from The University of Texas at Dallas in May 2005. Dr. Meghanathan has published more than 150 peer-reviewed articles (more than half of them being journal publications). He has also received federal education and research grants from the U. S. National Science Foundation, Army Research Lab and Air Force Research Lab. Dr. Meghanathan has been serving in the editorial board of several international journals and in the Technical Program Committees and Organization Committees of several international conferences. His research interests are Wireless Ad hoc Networks and Sensor Networks, Graph Theory and Network Science, Cyber Security, Machine Learning, Bioinformatics and Computational Biology. For more information, visit http://www.jsums.edu/nmeghanathan.
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