Autonomic Computing
Principles, Design and Implementation
Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Programming, Software Development, General Computing
| 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.
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.
