國立虎尾科技大學 |

QoS prediction in cloud and service computing = approaches and applications /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	QoS prediction in cloud and service computing/ by Yilei Zhang, Michael R. Lyu.
其他題名:	approaches and applications /
作者:	Zhang, Yilei.
其他作者:	Lyu, Michael R.
出版者:	Singapore :Springer Singapore : : 2017.,
面頁冊數:	xi, 122 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Quality of service (Computer networks) -
電子資源:	http://dx.doi.org/10.1007/978-981-10-5278-1
ISBN:	9789811052781

QoS prediction in cloud and service computing = approaches and applications /
Zhang, Yilei.

QoS prediction in cloud and service computingapproaches and applications /[electronic resource] :by Yilei Zhang, Michael R. Lyu. - Singapore :Springer Singapore :2017. - xi, 122 p. :ill., digital ;24 cm. - SpringerBriefs in computer science,2191-5768. - SpringerBriefs in computer science..

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.

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.

ISBN: 9789811052781

Standard No.: 10.1007/978-981-10-5278-1doiSubjects--Topical Terms:

1060135
Quality of service (Computer networks)

LC Class. No.: TK5105.548

Dewey Class. No.: 004.6782

QoS prediction in cloud and service computing = approaches and applications /
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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.
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