Autonomic Computing
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Autonomic Computing
Author: Philippe Lalanda
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-05-13
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.
Autonomic Computing
The complexity of modern computer networks and systems, combined with the extremely dynamic environments in which they operate, is beginning to outpace our ability to manage them. Taking yet another page from the biomimetics playbook, the autonomic computing paradigm mimics the human autonomic nervous system to free system developers and administrators from performing and overseeing low-level tasks. Surveying the current path toward this paradigm, Autonomic Computing: Concepts, Infrastructure, and Applications offers a comprehensive overview of state-of-the-art research and implementations in this emerging area. This book begins by introducing the concepts and requirements of autonomic computing and exploring the architectures required to implement such a system. The focus then shifts to the approaches and infrastructures, including control-based and recipe-based concepts, followed by enabling systems, technologies, and services proposed for achieving a set of "self-*" properties, including self-configuration, self-healing, self-optimization, and self-protection. In the final section, examples of real-world implementations reflect the potential of emerging autonomic systems, such as dynamic server allocation and runtime reconfiguration and repair. Collecting cutting-edge work and perspectives from leading experts, Autonomic Computing: Concepts, Infrastructure, and Applications reveals the progress made and outlines the future challenges still facing this exciting and dynamic field.
Autonomic Computing
This book introduces Autonomic Computing. This concept is a cornerstone of IBM's strategic initiative, and it offers great promise because autonomic computing systems have the ability to manage themselves and dynamically adapt to change in accordance with evolving or dynamic business policies and objectives. The term "autonomic" comes from the autonomic nervous system, which controls many organs and muscles in the human body. These systems can perform management activities based on situations they observe or sense in the IT environment. Rather than IT professionals initiating management activities, the system observes something about itself and acts accordingly. This allows the IT professional to focus on high-value tasks while the technology manages the more mundane operations. This book explains how this can be made to happen and the changes that need to be made to make it happen.
