Autonomic Computing

Principles, Design and Implementation

  • Philippe Lalanda
  • Julie A. McCann
  • Ada Diaconescu

Part of the Undergraduate Topics in Computer Science book series (UTICS)

Table of contents

  1. Front Matter
    Pages i-xv
  2. Philippe Lalanda, Julie A. McCann, Ada Diaconescu
    Pages 1-21
  3. Philippe Lalanda, Julie A. McCann, Ada Diaconescu
    Pages 23-55
  4. Philippe Lalanda, Julie A. McCann, Ada Diaconescu
    Pages 57-94
  5. Philippe Lalanda, Julie A. McCann, Ada Diaconescu
    Pages 95-128
  6. Philippe Lalanda, Julie A. McCann, Ada Diaconescu
    Pages 129-151
  7. Philippe Lalanda, Julie A. McCann, Ada Diaconescu
    Pages 153-183
  8. Philippe Lalanda, Julie A. McCann, Ada Diaconescu
    Pages 185-215
  9. Philippe Lalanda, Julie A. McCann, Ada Diaconescu
    Pages 217-234
  10. Philippe Lalanda, Julie A. McCann, Ada Diaconescu
    Pages 235-261
  11. Philippe Lalanda, Julie A. McCann, Ada Diaconescu
    Pages 263-278
  12. Back Matter
    Pages 279-288

About this book

Introduction

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.

Keywords

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

Authors and affiliations

  • Philippe Lalanda
    • 1
  • Julie A. McCann
    • 2
  • Ada Diaconescu
    • 3
  1. 1.Université Joseph FourierGrenobleFrance
  2. 2., Department of ComputingImperial College LondonLondonUnited Kingdom
  3. 3.INFRESTélécom ParisTechParisFrance

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4471-5007-7
  • Copyright Information Springer-Verlag London 2013
  • Publisher Name Springer, London
  • eBook Packages Computer Science
  • Print ISBN 978-1-4471-5006-0
  • Online ISBN 978-1-4471-5007-7
  • Series Print ISSN 1863-7310
  • About this book