Self-Aware Computing Systems

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Special Collection:e-book
Format: Book
Language:English
Published: Cham : Springer International Publishing, 2017
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Online Access:https://doi.org/10.1007/978-3-319-47474-8
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020 |a 978-3-319-47474-8 
024 7 |a 10.1007/978-3-319-47474-8  |2 doi 
040 |a Springer  |b hun  |c ELTE 
041 0 |a eng 
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082 0 4 |a 005.1  |2 23 
245 0 0 |a Self-Aware Computing Systems  |c edited by Samuel Kounev [et.al] 
260 |a Cham  |b Springer International Publishing  |c 2017 
300 |a XVIII, 722 p.  |b ill. 
336 |a szöveg  |b txt  |2 rdacontent 
337 |a számítógépes  |b c  |2 rdamedia 
338 |a távoli hozzáférés  |b cr  |2 rdacarrier 
347 |a szövegfájl  |b PDF  |2 rda 
505 0 |a Part I Introduction -- Part II System Architectures -- Part III Methods and Algorithms -- Part IV Applications and Case Studies -- Part V Outlook. 
520 |a This book provides formal and informal definitions and taxonomies for self-aware computing systems, and explains how self-aware computing relates to many existing subfields of computer science, especially software engineering. It describes architectures and algorithms for self-aware systems as well as the benefits and pitfalls of self-awareness, and reviews much of the latest relevant research across a wide array of disciplines, including open research challenges. The chapters of this book are organized into five parts: Introduction, System Architectures, Methods and Algorithms, Applications and Case Studies, and Outlook. Part I offers an introduction that defines self-aware computing systems from multiple perspectives, and establishes a formal definition, a taxonomy and a set of reference scenarios that help to unify the remaining chapters. Next, Part II explores architectures for self-aware computing systems, such as generic concepts and notations that allow a wide range of self-aware system architectures to be described and compared with both isolated and interacting systems. It also reviews the current state of reference architectures, architectural frameworks, and languages for self-aware systems. Part III focuses on methods and algorithms for self-aware computing systems by addressing issues pertaining to system design, like modeling, synthesis and verification. It also examines topics such as adaptation, benchmarks and metrics. Part IV then presents applications and case studies in various domains including cloud computing, data centers, cyber-physical systems, and the degree to which self-aware computing approaches have been adopted within those domains. Lastly, Part V surveys open challenges and future research directions for self-aware computing systems. It can be used as a handbook for professionals and researchers working in areas related to self-aware computing, and can also serve as an advanced textbook for lecturers and postgraduate studen 
580 |a Nyomtatott kiadás: ISBN 9783319474724 
580 |a Nyomtatott kiadás: ISBN 9783319474731 
580 |a Nyomtatott kiadás: ISBN 9783319837444 
506 |a Az e-könyvek a teljes ELTE IP-tartományon belül online elérhetők. 
598 |a könyv 
595 |a e-book 
650 0 |a Software engineering. 
650 0 4 |a szoftverfejlesztés 
650 0 |a Computer Communication Networks. 
650 0 |a Computer science. 
650 0 4 |a számítástudomány 
650 1 4 |a Software Engineering. 
650 2 4 |a Computer Communication Networks. 
650 2 4 |a Models and Principles. 
653 |a elektronikus könyv 
700 1 |a Kounev, Samuel  |e szerk. 
710 2 |a SpringerLink (Online service)  |e közreadó testület 
850 |a B2 
856 4 0 |y Online változat  |u https://doi.org/10.1007/978-3-319-47474-8 
264 1 |a Cham  |b Springer International Publishing  |b Imprint: Springer  |c 2017