Autonomic computing aims to simplify the management and maintenance of pervasive, ubiquitous systems by transferring low-level operational tasks from humans to the system itself, allowing people to focus on higher-level responsibilities. This is accomplished by creating self-managing systems that can self-configure, self-heal, self-optimize, and self-protect.
Trustworthy autonomic computing technologies are increasingly used in areas such as data center and cloud management, smart cities, and autonomous systems like driverless vehicles. Despite these advances, ensuring the trustworthiness of such systems remains a significant challenge. This book addresses the issues and solutions related to building reliable and consistent self-managing systems, offering methods and techniques to achieve trustworthy autonomic computing. It is essential for researchers, developers, and users to have confidence that these systems will function correctly under all possible conditions and environmental inputs.
The book is intended for researchers in autonomic computing and trustworthy autonomics, serving as a comprehensive resource for foundational concepts, proof-of-concept studies, and innovative techniques. It is also valuable for lecturers and students studying autonomic computing, autonomics, and multi-agent systems, providing accessible explanations, sample code, exercises, and practical demonstrations. Additionally, it serves as an ideal tutorial guide for independent learners, featuring clear diagrams to illustrate techniques and processes.
