This book provides formal and informal definitions and taxonomies for self-aware computing systems, and explains how self-aware computing relates to many existing subfields of computer science, especially software engineering. It describes architectures and algorithms for self-aware systems as well as the benefits and pitfalls of self-awareness, and reviews much of the latest relevant research across a wide array of disciplines, including open research challenges.
This book can be used as a handbook for professionals and researchers working in areas related to self-aware computing, and can also serve as an advanced textbook for lecturers and postgraduate students studying subjects like advanced software engineering, autonomic computing, self-adaptive systems, and data-center resource management. Each chapter is largely self-contained, and offers plenty of references for anyone wishing to pursue the topic more deeply.
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- Self-Aware Computing Community: Dagstuhl Seminar 15041 on "Model-driven Algorithms and Architectures for Self-Aware Computing Systems"
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