Trustworthy Autonomic Computing

264 Pages·2023·13.338 MB·English

by  Thaddeus Eze

Trustworthy Autonomic Computing
The concept of autonomic computing seeks to reduce the complexity of pervasively ubiquitous T Trustworthy Autonomic
r
system management and maintenance by shifting the responsibility for low-level tasks from u
s
humans to the system while allowing humans to concentrate on high-level tasks. This is t
achieved by building self-managing systems that are generally capable of self-configuring, w Computing
o
self-healing, self-optimising, and self-protecting.
r
t
Trustworthy autonomic computing technologies are being applied in datacentre and cloud h
y
management, smart cities and autonomous systems including driverless cars. However, there
A
are still significant challenges to achieving trustworthiness. This book covers challenges and
u
solutions in autonomic computing trustworthiness from methods and techniques to achieve t
o
consistent and reliable system self-management. Researchers, developers and users need to
n
be confident that an autonomic self-managing system will remain correct in the face of any o
m
possible contexts and environmental inputs.
i
c
The book is aimed at researchers in autonomic computing, autonomics and trustworthy
C
autonomics. This will be a go-to book for foundational knowledge, proof of concepts and novel
o Thaddeus Eze
trustworthy autonomic techniques and approaches. It will be useful to lecturers and students m
of autonomic computing, autonomics and multi-agent systems who need an easy-to-use text p
u
with sample codes, exercises, use-case demonstrations. This is also an ideal tutorial guide for
t
independent study with simple and well documented diagrams to explain techniques and in
processes. g

About the Author
Thaddeus Eze is a cybersecurity senior lecturer and researcher at the Computer Science
Department, University of Chester, UK. He is a 2004 graduate of Anambra State University,
Nigeria, with BSc (Upper 2nd Class) in Computer Science. He holds an MSc (with Distinction,
2010) in Mobile Computing and Communications and a PhD in Trustworthy Autonomics from
the University of Greenwich, London, UK.
The Institution of Engineering and Technology E
theiet.org z
978-1-78561-883-3 e
IET COMPUTING SERIES 30
Trustworthy Autonomic
Computing
Other volumes in this series:
Volume 1 Knowledge Discovery and Data Mining M.A. Bramer (Editor)
Volume 3 Troubled IT Projects: Prevention and turnaround J.M. Smith
Volume 4 UML for Systems Engineering: Watching the wheels, 2nd Edition J. Holt
Volume 5 Intelligent Distributed Video Surveillance Systems S.A. Velastin and P. Remagnino (Editors)
Volume 6 Trusted Computing C. Mitchell (Editor)
Volume 7 SysML for Systems Engineering J. Holt and S. Perry
Volume 8 Modelling Enterprise Architectures J. Holt and S. Perry
Volume 9 Model-Based Requirements Engineering J. Holt, S. Perry and M. Bownsword
Volume 13 Trusted Platform Modules: Why, when and how to use them A. Segall
Volume 14 Foundations for Model-based Systems Engineering: From Patterns to Models J. Holt, S. Perry and
M. Bownsword
Volume 15 Big Data and Software Defined Networks J.Taheri (Editor)
Volume 18 Modeling and Simulation of Complex Communication M. A. Niazi (Editor)
Volume 20 SysML for Systems Engineering: A Model-Based Approach, 3rd Edition J.Holt and S. Perry
Volume 22 Virtual Reality and Light Field Immersive Video Technologies for Real-World Applications G. Lafruit and
M. Tehrani
Volume 23 Data as Infrastructure for Smart Cities L. Suzuki and A. Finkelstein
Volume 24 Ultrascale Computing Systems J. Carretero, E. Jeannot and A. Zomaya
Volume 25 Big Data-Enabled Internet of Things M. Khan, S. Khan, A. Zomaya (Editors)
Volume 26 Handbook of Mathematical Models for Languages and Computation A. Meduna, P. Horácˇek, M. Tomko
Volume 29 Blockchains for Network Security: Principles, technologies and applications H. Huang, L. Wang, Y. Wu,
K. R. Choo (Editors)
Volume 32 Network Classification for Traffic Management: Anomaly detection, feature selection, clustering and
classification Z. Tari, A. Fahad, A. Almalawi and X. Yi
Volume 33 Edge Computing: Models, technologies and applications J.Taheri and S. Deng (Editors)
Volume 34 AI for Emerging Verticals: Human-robot computing, sensing and networking
M. Z. Shakir and N. Ramzan (Editors)
Volume 35 Big Data Recommender Systems Vol 1 & 2 O. Khalid, S. U. Khan, A. Y. Zomaya (Editors)
Volume 37 Handbook of Big Data Analytics Vol 1 & 2 V. Ravi and A. K. Cherukuri (Editors)
Volume 39 ReRAM-based Machine Learning H. Y, L. Ni and S. M. P. Dinakarrao
Volume 40 E-learning Methodologies: Fundamentals, technologies and applications M. Goyal, R. Krishnamurthi and
D. Yadav (Editors)
Volume 44 Streaming Analytics: Concepts, architectures, platforms, use cases and applications P. Raj,
C. Surianarayanan, K. Seerangan and G. Ghinea (Editors)
Volume 44 Streaming Analytics: Concepts, architectures, platforms, use cases and applications P. Raj, A. Kumar,
V. García Díaz and N. Muthuraman (Editors)
Volume 54 Intelligent Network Design Driven by Big Data Analytics, IoT, AI and Cloud Computing S. Kumar,
G. Mapp and K. Cergiz (Editors)
Volume 115 Ground Penetrating Radar: Improving sensing and imaging through numerical modelling
X. L. Travassos, M. F. Pantoja and N. Ida
Trustworthy Autonomic
Computing
Thaddeus Eze
The Institution of Engineering and Technology
Published by The Institution of Engineering and Technology, London, United Kingdom
The Institution of Engineering and Technology is registered as a Charity in England & Wales
(no. 211014) and Scotland (no. SC038698).
© The Institution of Engineering and Technology 2022
First published 2022
This publication is copyright under the Berne Convention and the Universal Copyright
Convention. All rights reserved. Apart from any fair dealing for the purposes of research or
private study, or criticism or review, as permitted under the Copyright, Designs and Patents
Act 1988, this publication may be reproduced, stored or transmitted, in any form or by
any means, only with the prior permission in writing of the publishers, or in the case of
reprographic reproduction in accordance with the terms of licences issued by the Copyright
Licensing Agency. Enquiries concerning reproduction outside those terms should be sent to
the publisher at the undermentioned address:
The Institution of Engineering and Technology
Futures Place
Kings Way, Stevenage
Herts, SG1 2UA, United Kingdom
www.theiet.org
While the author and publisher believe that the information and guidance given in this
work are correct, all parties must rely upon their own skill and judgement when making use
of them. Neither the author nor publisher assumes any liability to anyone for any loss or
damage caused by any error or omission in the work, whether such an error or omission is
the result of negligence or any other cause. Any and all such liability is disclaimed.
The moral rights of the author to be identified as author of this work have been asserted by
him in accordance with the Copyright, Designs and Patents Act 1988.
British Library Cataloguing in Publication Data
A catalogue record for this product is available from the British Library
ISBN 978-1-78561-883-3 (hardback)
ISBN 978-1-78561-884-0 (PDF)
Typeset in India by Exeter Premedia Services Private Limited
Printed in the UK by CPI Group (UK) Ltd, Croydon
Cover Image: MF3d / E+ via Getty Images
Dedication
To the memories of mum and dad. To my siblings. To my lovely wife, Ezinne,
and our three boys.
This page intentionally left blank
Contents
About the Author xi
Preface xiii
Acknowledgments xvii
1 Trustworthy autonomics primer 1
1.1 Introduction to autonomic computing 2
1.1.1 Autonomic computing definitions 2
1.1.2 Autonomic functionalities 5
1.1.3 The autonomic computing system 8
1.2 Foundations of trustworthy autonomics 9
1.2.1 Towards trustworthy autonomics 11
1.2.2 Pillars of trustworthy autonomic systems 14
1.3 Conclusion 17
2 Evolution of autonomic computing 19
2.1 Importance of understanding the evolution of autonomic computing 20
2.2 Autonomic architecture 20
2.3 Autonomic computing: trends and direction 25
2.3.1 Background 26
2.3.2 Autonomic computing in the first decade 30
2.3.3 Autonomic computing in the second decade 37
2.3.4 First and second decades of autonomic computing research
at a glance 43
2.4 Trends, direction and open challenges 45
2.4.1 Trends and direction 47
2.4.2 Open challenges 49
2.5 Conclusion 51
3 Autonomic enabling techniques 53
3.1 About autonomic enabling techniques 54
3.2 Simple exponential smoothing 54
3.2.1 Implementing an SES using python 55
3.2.2 Basic implementation of an SES using microsoft excel sheet 56
3.2.3 Implementing SES in autonomic computing 58
3.3 Dead-zone logic 59
3.3.1 Implementing dead-zone logic in autonomic computing 65
viii Trustworthy autonomic computing
3.4 Stigmergy 68
3.4.1 Natural stigmergy: wildlife 68
3.4.2 Natural stigmergy: humans 69
3.4.3 Stigmergy in autonomic systems 72
3.5 Policy autonomics 74
3.5.1 Policy-based networking 75
3.5.2 Policy-based autonomics 77
3.6 Utility function 79
3.6.1 UF in autonomic systems 82
3.7 Fuzzy logic 84
3.7.1 Moving vehicle case example 84
3.7.2 Fuzzy logic controller 86
3.7.3 Fuzzy logic in autonomic system 86
3.8 Autonomic nervous system 87
3.9 Combining autonomic techniques 89
3.10 Conclusion 91
4 Trustworthy autonomic computing 93
4.1 About trustworthy autonomic computing 94
4.2 Trustworthy autonomic computing vs trusted computing 94
4.3 Trustworthy autonomic architecture 97
4.3.1 TrAArch framework 99
4.3.2 Overview of the TrAArch architecture components 100
4.3.3 Other relevant [early] architectures 105
4.4 Conclusion 107
5 Trustworthy autonomic architecture implementations 109
5.1 Case example scenario 1: autonomic marketing system 111
5.1.1 Experimental environment 114
5.1.2 Results and evaluation 117
5.2 Case example scenario 2: self-adapting resource allocation 120
5.2.1 TrAArch simulator 122
5.2.2 Experimental environment 135
5.2.3 Simulation 140
5.2.4 Results and Analysis 146
5.3 Stability versus optimality 164
5.4 Conclusion 165
6 Multi- agent interoperability 167
6.1 Introduction to multi-agent interoperability 168
6.2 Multi-agent systems and multi-agent coordination 168
6.3 A review of autonomic interoperability solutions 171
6.4 The architecture-based interoperability 175
6.4.1 Scheduling and resource allocation 175
Contents ix
6.5 Complex interactions in multi-manager scenario 178
6.5.1 Simulation design 179
6.5.2 Autonomic manager logic 180
6.5.3 Simulation scenarios and metrics 184
6.5.4 Results analysis 188
6.6 Conclusion 194
7 Level of autonomicity 197
7.1 Introduction to level of autonomicity 198
7.2 Measuring LoA 200
7.2.1 Autonomic measuring metrics 204
7.2.2 Normalisation and scaling of autonomic metrics dimensions 206
7.3 Methodology for measuring LoA 207
7.3.1 A specific case method 211
7.3.2 A generic case method 212
7.4 Evaluating autonomic systems 215
7.5 Conclusion 216
8 Conclusions and future work 217
8.1 A case for trustworthy autonomics 218
8.2 The autonomic computing state of the art 219
8.3 Techniques that power autonomic computing 220
8.4 Trustworthy autonomic architecture 221
8.5 Interoperability 222
8.6 Level of autonomicity (LoA) 223
8.7 Future work 224
References 227
Index 241