QoS Prediction in Cloud and Service Computing
Approaches and Applications
(Sprache: Englisch)
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...
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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. Inhaltsverzeichnis zu „QoS Prediction in Cloud and Service Computing “
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.
Autoren-Porträt von Yilei Zhang, Michael R. Lyu
Yilei Zhang received his PhD in Computer Science from the Chinese University of Hong Kong. His industry-specific experience in cloud and big data spans several years as an IT professional. His research interests include big data, service computing and cloud computing. He has served as a reviewer for a number of international journals as well as conferences including TSE, TR, TSC, WWW, WSDM, KDD, ISSRE, etc. He received the best student paper award at the ICWS 2010.
Bibliographische Angaben
- Autoren: Yilei Zhang , Michael R. Lyu
- 2017, 1st ed. 2017, XI, 122 Seiten, 12 farbige Abbildungen, Masse: 15,6 x 23,6 cm, Kartoniert (TB), Englisch
- Verlag: Springer, Berlin
- ISBN-10: 9811052778
- ISBN-13: 9789811052774
- Erscheinungsdatum: 11.08.2017
Sprache:
Englisch
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