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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.
Über die Autorin bzw. den Autor:
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.
Michael R. Lyu received his PhD in Computer Science from the University of California, Los Angeles. He is currently a Professor at the Chinese University of Hong Kong’s Computer Science and Engineering Department. He has published 450 peer-reviewed journal and conference papers. His research interests include software reliability engineering, distributed systems, fault-tolerant computing, service computing, multimedia information retrieval, and machine learning. He was named as the IEEE Reliability Society Engineer of the Year in 2010. He is a fellow of the IEEE, ACM and AAAS.
Titel: QoS Prediction in Cloud and Service ...
Verlag: Springer
Erscheinungsdatum: 2017
Einband: Softcover
Zustand: New
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Expose readers to the very forefront of performance research in cloud computing  Presents three QoS prediction approaches in cloud and service computing  Provides comprehensive information on QoS-aware technologies in clo. Bestandsnummer des Verkäufers 150711004
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Taschenbuch. Zustand: Neu. Qos Prediction in Cloud and Service Computing | Approaches and Applications | Yilei Zhang (u. a.) | Taschenbuch | xi | Englisch | 2017 | Springer Singapore | EAN 9789811052774 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Bestandsnummer des Verkäufers 109603624
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 122 pp. Englisch. Bestandsnummer des Verkäufers 9789811052774
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Bestandsnummer des Verkäufers 9789811052774
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