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

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.

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.