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-managing systems that are generally capable of self-configuring, self-healing, self-optimising, and self-protecting. Trustworthy autonomic computing technologies are being applied in datacentre and cloud management, smart cities and autonomous systems including driverless cars.
However, there are still significant challenges to achieving trustworthiness. This book covers challenges and solutions in autonomic computing trustworthiness from methods and techniques to achieve consistent and reliable system self-management. Researchers, developers and users need to be confident that an autonomic self-managing system will remain correct in the face of any possible contexts and environmental inputs.
The book is aimed at researchers in autonomic computing, autonomics and trustworthy autonomics. This will be a go-to book for foundational knowledge, proof of concepts and novel trustworthy autonomic techniques and approaches. It will be useful to lecturers and students of autonomic computing, autonomics and multi-agent systems who need an easy-to-use text with sample codes, exercises, use-case demonstrations. This is also an ideal tutorial guide for independent study with simple and well documented diagrams to explain techniques and processes.
This book covers challenges and solutions of autonomic computing trustworthiness from methods and techniques to achieve consistent and reliable system self-management. This is an ideal tutorial guide for independent study with simple and well documented diagrams to explain techniques and processes.
- 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
Thaddeus Eze is a cybersecurity senior lecturer and researcher at the Computer Science Department, University of Chester, UK. He is the programme leader for MSc Cybersecurity (Conversion) and the postgraduate assessment officer for the Computer Science department. His research interests include cybersecurity awareness and training, trustworthy autonomic computing, ethical hacking, cryptography, and digital forensics. He is a member of CIISec and was the Vice Chair of the IEEE Young Professionals, UK & Ireland Section from 2014 to 2022. He's the Convener and organiser of the IEEE UK & Ireland YP Postgraduate STEM Research Symposium (three successful editions already organised). He was actively involved in organising the first ever UK Pitch Bootcamp and the IEEE Professional Development Networking Workshop 2017. 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.
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