QoS Prediction in Cloud and Service Computing - Approaches and Applications
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Bester Preis: € 41,75 (vom 02.09.2017)1
QoS Prediction in Cloud and Service Computing - Approaches and Applications
EN NW EB DL
ISBN: 9789811052781 bzw. 9811052786, in Englisch, Springer-Verlag, neu, E-Book, elektronischer Download.
Lieferung aus: Deutschland, E-Book zum Download.
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. 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 Kongs 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.
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. 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 Kongs 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.
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QoS Prediction in Cloud and Service Computing (2017)
EN NW EB DL
ISBN: 9789811052781 bzw. 9811052786, in Englisch, Springer, Springer, Springer, neu, E-Book, elektronischer Download.
Lieferung aus: Vereinigtes Königreich Großbritannien und Nordirland, in-stock.
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.
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.
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QoS Prediction in Cloud and Service Computing als eBook von Yilei Zhang, Michael R. Lyu
EN NW EB DL
ISBN: 9789811052781 bzw. 9811052786, in Englisch, neu, E-Book, elektronischer Download.
QoS Prediction in Cloud and Service Computing ab 43.49 EURO Approaches and Applications SpringerBriefs in Computer Science, QoS Prediction in Cloud and Service Computing ab 43.49 EURO Approaches and Applications SpringerBriefs in Computer Science.
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