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Autonomic Computing: Principles, Design and Implementation: Undergraduate Topics in Computer Science

Autor Philippe Lalanda, Julie A. McCann, Ada Diaconescu
en Limba Engleză Paperback – 28 mai 2013
This textbook provides a practical perspective on autonomic computing. Through the combined use of examples and hands-on projects, the book enables the reader to rapidly gain an understanding of the theories, models, design principles and challenges of this subject while building upon their current knowledge. Features: provides a structured and comprehensive introduction to autonomic computing with a software engineering perspective; supported by a downloadable learning environment and source code that allows students to develop, execute, and test autonomic applications at an associated website; presents the latest information on techniques implementing self-monitoring, self-knowledge, decision-making and self-adaptation; discusses the challenges to evaluating an autonomic system, aiding the reader in designing tests and metrics that can be used to compare systems; reviews the most relevant sources of inspiration for autonomic computing, with pointers towards more extensive specialty literature.
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Specificații

ISBN-13: 9781447150060
ISBN-10: 1447150066
Pagini: 294
Ilustrații: XV, 288 p. 88 illus.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 4.63 kg
Ediția:2013
Editura: SPRINGER LONDON
Colecția Springer
Seria Undergraduate Topics in Computer Science

Locul publicării:London, United Kingdom

Public țintă

Upper undergraduate

Descriere

Autonomic computing is changing the way software systems are being developed, introducing the goal of self-managed computing systems with minimal need for human input.
This easy-to-follow, classroom-tested textbook/reference provides a practical perspective on autonomic computing. Through the combined use of examples and hands-on projects, the book enables the reader to rapidly gain an understanding of the theories, models, design principles and challenges of this subject while building upon their current knowledge; thus reinforcing the concepts of autonomic computing and self-management.
Topics and features: provides a structured and comprehensive introduction to autonomic computing with a software engineering perspective; supported by a downloadable learning environment and source code that allows students to develop, execute, and test autonomic applications at an associated website; presents the latest information on techniques implementing self-monitoring, self-knowledge, decision-making and self-adaptation; discusses the challenges to evaluating an autonomic system, aiding the reader in designing tests and metrics that can be used to compare autonomic computing systems; reviews the most relevant sources of inspiration for autonomic computing, with pointers towards more extensive specialty literature; ideal for a 10-week lecture programme.
This concise primer and practical guide will be of great use to students, researchers and practitioners alike, demonstrating how to better architect robust yet flexible software systems capable of meeting the computing demands for today and in the future.

Cuprins

Software Engineering to Autonomic Computing
Autonomic Systems
Sources of Inspiration for Autonomic Computing
Autonomic Computing Architectures
The Monitoring Function
The Adaptation Function
The Decision Function
Evaluation Issues
Autonomic Mediation in Cilia
Future of Autonomic Computing and Conclusions
Learning Environment

Notă biografică

Dr. Philippe Lalanda is a professor of software engineering at the Joseph Fourier University, Grenoble, France.
Dr. Julie A. McCann is a Reader in Computer Systems at Imperial College London, UK.
Dr. Ada Diaconescu is a lecturer (maître de conférences) in the Department of Computing and Networks at Télécom ParisTech, France.

Textul de pe ultima copertă

Autonomic computing is changing the way software systems are being developed, introducing the goal of self-managed computing systems with minimal need for human input.
This easy-to-follow, classroom-tested textbook/reference provides a practical perspective on autonomic computing. Through the combined use of examples and hands-on projects, the book enables the reader to rapidly gain an understanding of the theories, models, design principles and challenges of this subject while building upon their current knowledge; thus reinforcing the concepts of autonomic computing and self-management.
Topics and features:
  • Provides a structured and comprehensive introduction to autonomic computing with a software engineering perspective
  • Supported by a downloadable learning environment and source code that allows students to develop, execute, and test autonomic applications at an associated website
  • Presents the latest information on techniques implementing self-monitoring, self-knowledge, decision-making and self-adaptation
  • Discusses the challenges to evaluating an autonomic system, aiding the reader in designing tests and metrics that can be used to compare autonomic computing systems
  • Reviews the most relevant sources of inspiration for autonomic computing, with pointers towards more extensive specialty literature
  • Ideal for a 10-week lecture programme
This concise primer and practical guide will be of great use to students, researchers and practitioners alike, demonstrating how to better architect robust yet flexible software systems capable of meeting the computing demands for today and in the future.

Caracteristici

The first practical guide to autonomic computing for advanced students and researchers alike
Presents classroom-tested examples and hands-on bounded projects that illustrate the concepts in a concrete fashion
Provides software for a learning environment for developing, executing and testing autonomic applications