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Quality-aware Scheduling for Key-value Data Stores

  • Chen Xu
  • Aoying Zhou

Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Chen Xu, Aoying Zhou
    Pages 1-9
  3. Chen Xu, Aoying Zhou
    Pages 11-23
  4. Chen Xu, Aoying Zhou
    Pages 25-35
  5. Chen Xu, Aoying Zhou
    Pages 37-63
  6. Chen Xu, Aoying Zhou
    Pages 65-81
  7. Chen Xu, Aoying Zhou
    Pages 83-94
  8. Chen Xu, Aoying Zhou
    Pages 95-97

About this book

Introduction

Key-value stores, which are commonly used as data platform for various web applications, provide a distributed solution for cloud computing and big data management.  In modern web applications, user experience satisfaction determines their success​. In real application, different web queries or users produce different expectations in terms of query latency (i.e., Quality of Service (QoS)) and data freshness (i.e., Quality of Data (QoD)).  Hence, the question of how to optimize QoS and QoD by scheduling queries and updates in key-value stores has become an essential research issue. This book comprehensively illustrates quality-ware scheduling in key-value stores. In addition, it provides scheduling strategies and a prototype framework for a quality-aware scheduler, as well as a demonstration of online applications. The book offers a rich blend of theory and practice, making it suitable for students, researchers and practitioners interested in distributed systems, NoSQL key-value stores and scheduling.​

Keywords

Data Consistency Key-Value Stores Quality of Data Quality of Service Scheduling

Authors and affiliations

  • Chen Xu
    • 1
  • Aoying Zhou
    • 2
  1. 1.Institute for Data Science and EngineeringEast China Normal UniversityShanghaiChina
  2. 2.Institute for Data Science and EngineeringEast China Normal UniversityShanghaiChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-662-47306-1
  • Copyright Information The Author(s) 2015
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-662-47305-4
  • Online ISBN 978-3-662-47306-1
  • Series Print ISSN 2191-5768
  • Series Online ISSN 2191-5776
  • Buy this book on publisher's site
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