QoS Prediction in Cloud and Service Computing : Approaches and Applications

This book offers a systematic and practical overview of Quality of Service prediction in cloud and service computing. Intended to thoroughly prepare the reader for research in cloud performance, the book first identifies common problems in QoS prediction and proposes three QoS prediction models to a...

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Main Authors: Zhang, Yilei, Lyu, Michael R. (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Singapore Springer Singapore 2017, 2017
Edition:1st ed. 2017
Series:SpringerBriefs in Computer Science
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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245 0 0 |a QoS Prediction in Cloud and Service Computing  |h Elektronische Ressource  |b Approaches and Applications  |c by Yilei Zhang, Michael R. Lyu 
250 |a 1st ed. 2017 
260 |a Singapore  |b Springer Singapore  |c 2017, 2017 
300 |a XI, 122 p. 41 illus., 12 illus. in color  |b online resource 
505 0 |a 1. Introduction -- 2. Neighborhood-Based QoS Prediction -- 3. Time-Aware Model-Based QoS Prediction -- 4. Online QoS Prediction -- 5. QoS-AwareWeb Service Searching -- 6. QoS-Aware Byzantine Fault Tolerance -- 7. Conclusion and Discussion 
653 |a Information Systems Applications (incl. Internet) 
653 |a Software engineering 
653 |a Operating systems (Computers) 
653 |a Performance and Reliability 
653 |a Software Engineering 
700 1 |a Lyu, Michael R.  |e [author] 
710 2 |a SpringerLink (Online service) 
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989 |b Springer  |a Springer eBooks 2005- 
490 0 |a SpringerBriefs in Computer Science 
856 |u https://doi.org/10.1007/978-981-10-5278-1?nosfx=y  |x Verlag  |3 Volltext 
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520 |a This book offers a systematic and practical overview of Quality of Service prediction in cloud and service computing. Intended to thoroughly prepare the reader for research in cloud performance, the book first identifies common problems in QoS prediction and proposes three QoS prediction models to address them. Then it demonstrates the benefits of QoS prediction in two QoS-aware research areas. Lastly, it collects large-scale real-world temporal QoS data and publicly releases the datasets, making it a valuable resource for the research community. The book will appeal to professionals involved in cloud computing and graduate students working on QoS-related problems.