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Computer Science - Software Engineering | Autonomic Computing - Principles, Design and Implementation

Autonomic Computing

Principles, Design and Implementation

Lalanda, Philippe, McCann, Julie A., Diaconescu, Ada

2013, XV, 288 p. 88 illus.

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  • The first practical guide to autonomic computing for advanced students and researchers alike
  • Presents classroom-tested examples and hands-on bounded projects that illustrate the concepts in a concrete fashion
  • Provides software for a learning environment for developing, executing and testing autonomic applications

Autonomic computing is changing the way software systems are being developed, introducing the goal of self-managed computing systems with minimal need for human input.

This easy-to-follow, classroom-tested textbook/reference 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; thus reinforcing the concepts of autonomic computing and self-management.

Topics and 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 autonomic computing systems
  • Reviews the most relevant sources of inspiration for autonomic computing, with pointers towards more extensive specialty literature
  • Ideal for a 10-week lecture programme

This concise primer and practical guide will be of great use to students, researchers and practitioners alike, demonstrating how to better architect robust yet flexible software systems capable of meeting the computing demands for today and in the future.

Content Level » Upper undergraduate

Keywords » Autonomic Computing - Dynamic Computing - Self-adaptive - Self-configuration - Self-management

Related subjects » Artificial Intelligence - Communication Networks - Software Engineering

Table of contents 

Software Engineering to Autonomic Computing

Autonomic Systems

Sources of Inspiration for Autonomic Computing

Autonomic Computing Architectures

The Monitoring Function

The Adaptation Function

The Decision Function

Evaluation Issues

Autonomic Mediation in Cilia

Future of Autonomic Computing and Conclusions

Learning Environment

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