Adaptive, Dynamic, and Resilient Systems
As the complexity of today's networked computer systems grows, they become increasingly difficult to understand, predict, and control. Addressing these challenges requires new approaches to building these systems. Adaptive, Dynamic, and Resilient Systems supplies readers with various perspectives of the critical infrastructure that systems of netwo
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Adaptive, Dynamic, and Resilient Systems
As the complexity of today's networked computer systems grows, they become increasingly difficult to understand, predict, and control. Addressing these challenges requires new approaches to building these systems. Adaptive, Dynamic, and Resilient Systems supplies readers with various perspectives of the critical infrastructure that systems of netwo
77.99 In Stock
Adaptive, Dynamic, and Resilient Systems

Adaptive, Dynamic, and Resilient Systems

Adaptive, Dynamic, and Resilient Systems

Adaptive, Dynamic, and Resilient Systems

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Overview

As the complexity of today's networked computer systems grows, they become increasingly difficult to understand, predict, and control. Addressing these challenges requires new approaches to building these systems. Adaptive, Dynamic, and Resilient Systems supplies readers with various perspectives of the critical infrastructure that systems of netwo

Product Details

ISBN-13: 9781040197776
Publisher: CRC Press
Publication date: 06/23/2014
Sold by: Barnes & Noble
Format: eBook
Pages: 378
File size: 9 MB

About the Author

Niranjan Suri is a research scientist at the Florida Institute for Human & Machine Cognition (IHMC) and also a visiting scientist at the U.S. Army Research Laboratory, Adelphi, Maryland. He received his Ph.D. in computer science from Lancaster University, England, and his M.Sc. and B.Sc. in computer science from the University of West Florida, Pensacola. His current research activity is focused on the notion of agile computing, which supports the opportunistic discovery and exploitation of resources in highly dynamic networked environments. His other research interests include coordination algorithms, distributed systems, networking, communication protocols, virtual machines, and software agents.
Giacomo Cabri received the Laurea degree in computer science engineering from the University of Bologna in July 1995. In February 2000 he received the PhD in information engineering from the Dipartimento di Scienze dell'Ingegneria of the Universita di Modena e Reggio Emilia. He received a research contract by the Dipartimento di Scienze dell'Ingegneria of the Universita di Modena e Reggio Emilia, from January 1, 2001, to October 31, 2001. From November 1, 2001, to December 20, 2006, he was a research associate at the Facolta di Ingegneria of the Universita degli studi di Modena e Reggio Emilia, SSD ING-INF/05, position confirmed from November 1, 2004. From December 21, 2006, he has been an Associate Professor, SSD ING-INF/05 and his affiliation is the Dipartimento di Scienze Fisiche, Informatiche e Matematiche of the Universita di Modena e Reggio Emilia. He teaches different courses in the field of computer science and information technology, both basic ones and advanced ones. His research activities are mainly related to the following areas:

  • Agents: base models and coordination protocols
  • Autonomic computing
  • Web applications
  • Mobile computing

In these areas, he

Table of Contents

Introduction. Modeling Adaptive Software Systems. Service-Oriented Software Engineering Lifecycles. On Measuring Resilience in Command and Control Architectures. Resiliency and Robustness of Complex Systems and Networks. Resilient and Adaptive Networked Systems. Bringing Adaptiveness and Resilience to e-Health. Agile Computing. A Pattern-Based Architectural Style for Self-Organizing Software Systems. Adaptation and Resilience of Self-Organizing Electronic Institutions. Assessing the Resilience of Self-Organizing Systems. Leveraging ICT to Enable e-Maintenance for Automated Machines. Using Planning to Adapt to Dynamic Environments. Policy-Based Governance of Complex Distributed Systems. Adaptive and Resilient Computational Resource Allocation Inspired by Economics. Instrumentation-Based Resource Control.
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