eBook Biologically Inspired Networking and Sensing: Algorithms and Architectures, 1st Edition

  • Pietro Lio
  • Published By:
  • ISBN-10: 1613500939
  • ISBN-13: 9781613500934
  • DDC: 004.6
  • Grade Level Range: College Freshman - College Senior
  • 312 Pages | eBook
  • Original Copyright 2012 | Published/Released November 2012
  • This publication's content originally published in print form: 2012
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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.

Table of Contents

Front Cover.
Title Page.
Copyright Page.
Editorial Advisory Board.
List of Reviewers.
Table of Contents.
1: New Biologically Inspired Architectures.
2: A Networking Paradigm Inspired by Cell Communication Mechanisms.
3: Organic Network Control: Turning Standard Protocols into Evolving Systems.
4: Robust Network Services with Distributed Code Rewriting.
5: Neural Networks in Cognitive Science: An Introduction.
6: The Dendritic Cell Algorithm for Intrusion Detection.
7: Bio-Inspired Network Resource Optimization.
8: TCP Symbiosis: Bio-Inspired Congestion Control Mechanism for TCP.
9: From Local Growth to Global Optimization in Insect Built Networks.
10: Network Energy Driven Wireless Sensor Networks.
11: Congestion Control in Wireless Sensor Networks Based on the Lotka Volterra Competition Model.
12: Biologically Inspired Routing Protocols.
13: Autonomously Evolving Communication Protocols: The Case of Multi-Hop Broadcast.
14: Application of Genetic Algorithms for Optimization of Anycast Routing in Delay and Disruption Tolerant Networks.
15: Data Highways: An Activator–Inhibitor–Based Approach for Autonomic Data Dissemination in Ad Hoc Wireless Networks.
16: Scented Node Protocol for MANET Routing.
Compilation of References.
About the Contributors.