Context-Aware Computing and Self-Managing Systems Contributor(s): Dargie, Waltenegus (Editor) |
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ISBN: 0367385848 ISBN-13: 9780367385842 Publisher: CRC Press OUR PRICE: $75.95 Product Type: Paperback - Other Formats Published: October 2019 |
Additional Information |
BISAC Categories: - Mathematics - Computers | Computer Science - Technology & Engineering | Industrial Health & Safety |
Dewey: 004 |
Series: Chapman & Hall/CRC Studies in Informatics |
Physical Information: 0.9" H x 5.7" W x 9.2" (1.75 lbs) 408 pages |
Descriptions, Reviews, Etc. |
Publisher Description: Bringing together an extensively researched area with an emerging research issue, Context-Aware Computing and Self-Managing Systems presents the core contributions of context-aware computing in the development of self-managing systems, including devices, applications, middleware, and networks. The expert contributors reveal the usefulness of context-aware computing in developing autonomous systems that have practical application in the real world. The first chapter of the book identifies features that are common to both context-aware computing and autonomous computing. It offers a basic definition of context-awareness, covers fundamental aspects of self-managing systems, and provides several examples of context information and self-managing systems. Subsequent chapters on context-awareness demonstrate how a context can be employed to make systems smart, how a context can be captured and represented, and how dynamic binding of context sources can be possible. The chapters on self-management illustrate the need for implicit knowledge to develop fault-tolerant and self-protective systems. They also present a higher-level vision of future large-scale networks. Through various examples, this book shows how context-aware computing can be used in many self-managing systems. It enables researchers of context-aware computing to identify potential applications in the area of autonomous computing. The text also supports researchers of autonomous computing in defining, modeling, and capturing dynamic aspects of self-managing systems. |