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 (maitre de conferences) in the Department of Computing and Networks at Telecom ParisTech, France.
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