Trustworthy Autonomic Computing

The concept of autonomic computing seeks to reduce the complexity of pervasively ubiquitous system management and maintenance by shifting the responsibility for low-level tasks from humans to the system while allowing humans to concentrate on high-level tasks. This is achieved by building self-manag...

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Bibliographic Details
Main Author Eze, Thaddeus
Format eBook
LanguageEnglish
Published Stevenage The Institution of Engineering and Technology 2022
Institution of Engineering and Technology (The IET)
Institution of Engineering & Technology
Institution of Engineering and Technology
Edition1
SeriesComputing and Networks
Subjects
Autonomic computing
Computer networking & communications
COMPUTERS
General Engineering & Project Administration
General References
Networking
Software Engineering
Online AccessGet full text
ISBN1785618830
9781785618833
DOI10.1049/PBPC030E

Cover

Table of Contents:
  • Chapter 1: Trustworthy autonomics primer -- Chapter 2: Evolution of autonomic computing -- Chapter 3: Autonomic enabling techniques -- Chapter 4: Trustworthy autonomic computing -- Chapter 5: Trustworthy autonomic architecture implementations -- Chapter 6: Multi-agent interoperability -- Chapter 7: Level of autonomicity -- Chapter 8: Conclusions and future work
  • Title Page Preface Table of Contents 1. Trustworthy Autonomics Primer 2. Evolution of Autonomic Computing 3. Autonomic Enabling Techniques 4. Trustworthy Autonomic Computing 5. Trustworthy Autonomic Architecture Implementations 6. Multi-Agent Interoperability 7. Level of Autonomicity 8. Conclusions and Future Work References Index
  • 8.3 Techniques that power autonomic computing -- 8.4 Trustworthy autonomic architecture -- 8.5 Interoperability -- 8.6 Level of autonomicity (LoA) -- 8.7 Future work -- References -- Index
  • Intro -- Contents -- Preface -- About the Author -- Chapter 1: Trustworthy autonomics primer -- 1.1 Introduction to autonomic computing -- 1.2 Foundations of trustworthy autonomics -- Chapter 2: Evolution of autonomic computing -- 2.1 Importance of understanding the evolution of autonomic computing -- 2.2 Autonomic Architecture -- 2.3 Autonomic computing: trends and direction -- 2.4 Trends, direction and open challenges -- 2.5 Conclusion -- Chapter 3: Autonomic enabling techniques -- 3.1 About autonomic enabling techniques -- 3.2 Simple exponential smoothing -- 3.3 Dead-zone logic -- 3.4 Stigmergy -- 3.5 Policy autonomics -- 3.6 Utility function -- 3.7 Fuzzy logic -- 3.8 Autonomic nervous system -- 3.9 Combining autonomic techniques -- 3.10 Conclusion -- Chapter 4: Trustworthy autonomic computing -- 4.1 About trustworthy autonomic computing -- 4.2 Trustworthy autonomic computing vs trusted computing -- 4.3 Trustworthy autonomic architecture -- 4.4 Conclusion -- Chapter 5: Trustworthy autonomic architecture implementations -- 5.1 Case example scenario 1: autonomic marketing system -- 5.2 Case example scenario 2: self-adapting resource allocation -- 5.3 Stability versus optimality -- 5.4 Conclusion -- Chapter 6: Multi-agent interoperability -- 6.1 Introduction to multi-agent interoperability -- 6.2 Multi-agent systems and multi-agent coordination -- 6.3 A review of autonomic interoperability solutions -- 6.4 The architecture-based interoperability -- 6.5 Complex interactions in multi-manager scenario -- 6.6 Conclusion -- Chapter 7: Level of autonomicity -- 7.1 Introduction to level of autonomicity -- 7.2 Measuring LoA -- 7.3 Methodology for measuring LoA -- 7.4 Evaluating autonomic systems -- 7.5 Conclusion -- Chapter 8: Conclusions and future work -- 8.1 A case for trustworthy autonomics -- 8.2 The autonomic computing state of the art