Advances in biologically inspired information systems : models, methods, and tools
著者
書誌事項
Advances in biologically inspired information systems : models, methods, and tools
（Studies in computational intelligence, v. 69）
Springer, c2007
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注記
"This book collects extended versions of selected outstanding papers originally submitted to BIONETICS 2006"--Pref
Includes bibliographical references
"with 132 figures and 14 tables" -- Title page
内容説明・目次
内容説明
Technology is taking us to a world where myriads of networked devices interact with the physical world in multiple ways and at multiple scales. This book presents a comprehensive overview of the most promising research directions in the area of bio-inspired computing. According to the broad spectrum addressed by the different chapters, a rich variety of biological principles and their application to ICT systems are presented.
目次
Self-Organizing Network Environments.- Bio-inspired Framework for Autonomic Communication Systems.- Towards a Biologically-inspired Architecture for Self-Regulatory and Evolvable Network Applications.- Biologically Inspired Synchronization for Wireless Networks.- Bio-Inspired Congestion Control: Conceptual Framework, Algorithm and Discussion.- Self-Organized Network Security Facilities based on Bio-inspired Promoters and Inhibitors.- System Design and Programming.- Context Data Dissemination in the Bio-inspired Service Life Cycle.- Eigenvector Centrality in Highly Partitioned Mobile Networks: Principles and Applications.- Toward Organization-Oriented Chemical Programming: A Case Study with the Maximal Independent Set Problem.- Evolving Artificial Cell Signaling Networks: Perspectives and Methods.- Sensor and Actor Networks.- Immune System-based Energy Efficient and Reliable Communication in Wireless Sensor Networks.- A Bio-Inspired Architecture for Division of Labour in SANETs.- A Pragmatic Model of Attention and Anticipation for Active Sensor Systems.- Search and Optimization.- Self-Organization for Search in Peer-to-Peer Networks.- A Bio-Inspired Location Search Algorithm for Peer to Peer Networks.- Ant Colony Optimization and its Application to Regular and Dynamic MAX-SAT Problems.
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