Autonomic Computing

Principles, Design and Implementation

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Programming, Software Development, General Computing
Cover of the book Autonomic Computing by Philippe Lalanda, Julie A. McCann, Ada Diaconescu, Springer London
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Author: Philippe Lalanda, Julie A. McCann, Ada Diaconescu ISBN: 9781447150077
Publisher: Springer London Publication: May 13, 2013
Imprint: Springer Language: English
Author: Philippe Lalanda, Julie A. McCann, Ada Diaconescu
ISBN: 9781447150077
Publisher: Springer London
Publication: May 13, 2013
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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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