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.
Table of Contents
The Role of Context-Aware Computing in Developing Self-Managing Systems. Verifying Nursing Activities Based on Workflow Model. A Taxonomy of Service Discovery Systems. Managing Distributed and Heterogeneous Context for Ambient Intelligence. Dynamic Content Negotiation in Web Environments. The Road toward Self-Management in Communication Networks. Policy-Based Self-Management in Wireless Networks. Autonomous Machine Learning Networks. Probabilistic Fault Management.