Название: Trustworthy Autonomic ComputingАвтор: Thaddeus Eze
Издательство: The Institution of Engineering and Technology
Серия: IET Computing Series
Год: 2022
Страниц: 264
Язык: английский
Формат: pdf (true)
Размер: 13.3 MB
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.
SES is one out of three types of exponential smoothing techniques. It is suitable for series that are unpredictable, i.e., series with no trend or seasonality. Holt’s exponential smoothing is suitable for series with trend and no seasonality while Winter’s exponential smoothing is suitable for series with trend and seasonality. These can be implemented in Python using the Statsmodels package.
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 has been planned to have a very wide appeal and is targeted at:
– Early researchers in autonomic and trustworthy autonomic computing. This offers a go-to book for foundational knowledge, proof of concepts and novel trustworthy autonomic techniques and approaches.
– Teachers and students of autonomic computing and multi-agent systems who need an easy-to-use text with sample codes, exercises, use-case demonstrations; it is also suitable for self-teaching.
– Early programmers who require accessible pseudocode and code examples for application demonstrations.
– Others studying or researching other areas of computer science and engineering requiring a basic grounding in the techniques presented in the book.
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