Biologically Inspired Networking and Sensing: Algorithms and Architectures

ISBN 10: 1613500920 / ISBN 13: 9781613500927

Published by Medical Information Science Reference, 2011

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Bibliographic Details

• Title: Biologically Inspired Networking and Sensing: Algorithms and Architectures
• Publisher: Medical Information Science Reference
• Publication Date: 2011
• Language: English
• ISBN 10: 1613500920
• ISBN 13: 9781613500927
• Binding: Hardcover
• Condition: New

About this title

Synopsis

Despite their widespread impact, computer networks that provide the foundation for the World Wide Web and Internet have many limitations. These networks are vulnerable to security threats, break easily, and have a limited ability to respond to changing conditions. Recent research on overcoming these limitations has used biological systems for inspiration, resulting in the development of biologically-inspired computer networks. These networks are designed and developed using principles that are commonly found in natural and biological systems. Biologically Inspired Networking and Sensing: Algorithms and Architectures offers current perspectives and trends in biologically-inspired networking, exploring various approaches aimed at improving network paradigms. Research contained within this compendium of papers and surveys introduces studies in the fields of communication networks, performance modeling, and distributed computing, as well as new advances in networking.

About the Author

Pietro Lio is a Senior Lecturer in the Computer Laboratory which is the department of Computer Science of the University of Cambridge and a member of the Artificial Intelligence group of the Computer Laboratory. He has an interdisciplinary approach to research and teaching and holds a PhD in Complex Systems and Non Linear Dynamics (School of Informatics, dept of Engineering of the University of Firenze, Italy) and a PhD in (Theoretical) Genetics (University of Pavia, Italy). His current research interest is the investigation of biomedical processes employing a combination of techniques, ranging from machine learning to deterministic and stochastic models.

Dinesh Verma is a researcher and department group manager in the IT & Wireless Convergence area at IBM T J Watson Research Center, Hawthorne, New York. He received his doctorate in Computer Networking from University of California Berkeley in 1992, the Bachelor's in Computer Science from Indian Institute of Technology, Kanpur, India in 1987 and a Master's in Management of Technology from Polytechnic University, Brooklyn, NY in 1998. He holds over thirty US patents related to computer networks and has authored over sixty papers and eight books in the area. He is the program manager for the US/UK International Technology Alliance in Network Sciences. He is a fellow of the IEEE and has served in various program committees and technical committees. His research interests include topics in wireless networks, network management, distributed computing and autonomic systems.