SpringerBriefs in Computer Science

QoS Prediction in Cloud and Service Computing

Approaches and Applications

Authors: Zhang, Yilei, Lyu, Michael R.

  • 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 cloud applications

Buy this book

eBook 44,02 €
price for Spain (gross)
  • ISBN 978-981-10-5278-1
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover 57,19 €
price for Spain (gross)
  • ISBN 978-981-10-5277-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this book

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. 

About the authors

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.

Table of contents (7 chapters)

  • Introduction

    Zhang, Yilei (et al.)

    Pages 1-13

    Preview Buy Chapter 30,19 €
  • Neighborhood-Based QoS Prediction

    Zhang, Yilei (et al.)

    Pages 15-34

    Preview Buy Chapter 30,19 €
  • Time-Aware Model-Based QoS Prediction

    Zhang, Yilei (et al.)

    Pages 35-53

    Preview Buy Chapter 30,19 €
  • Online QoS Prediction

    Zhang, Yilei (et al.)

    Pages 55-80

    Preview Buy Chapter 30,19 €
  • QoS-Aware Web Service Searching

    Zhang, Yilei (et al.)

    Pages 81-103

    Preview Buy Chapter 30,19 €

Buy this book

eBook 44,02 €
price for Spain (gross)
  • ISBN 978-981-10-5278-1
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover 57,19 €
price for Spain (gross)
  • ISBN 978-981-10-5277-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
QoS Prediction in Cloud and Service Computing
Book Subtitle
Approaches and Applications
Authors
Series Title
SpringerBriefs in Computer Science
Copyright
2017
Publisher
Springer Singapore
Copyright Holder
The Author(s)
eBook ISBN
978-981-10-5278-1
DOI
10.1007/978-981-10-5278-1
Softcover ISBN
978-981-10-5277-4
Series ISSN
2191-5768
Edition Number
1
Number of Pages
XI, 122
Number of Illustrations and Tables
29 b/w illustrations, 12 illustrations in colour
Topics