Quality-aware scheduling for key-value data stores [electronic resource] / Chen Xu, Aoying Zhou.
Xu, Chen, author.; Zhou, Aoying, 1965- author.
2015
QA76.53 .X8 2015eb
Available Online

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Title Quality-aware scheduling for key-value data stores [electronic resource] / Chen Xu, Aoying Zhou.
Author Xu, Chen, author.
ISBN 9783662473061 electronic book
3662473062 electronic book
9783662473054
Published Heidelberg : Springer, 2015.
Language English
Description 1 online resource (xi, 97 pages) : illustrations.
Call Number QA76.53 .X8 2015eb
Dewey Decimal Classification 005.4/34
Summary 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.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed June 10, 2015).
Added Author Zhou, Aoying, 1965- author.
Series SpringerBriefs in computer science.
Available in Other Form Quality-aware Scheduling for Key-value Data Stores
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Preface; Acknowledgments; Contents; 1 Introduction; 1.1 Application Scenarios; 1.2 The Research Significance and Challenges; 1.3 Implementation Framework; 1.4 Overview of the Book; References; 2 Literature and Research Review; 2.1 Metrics for Quality-Aware Scheduling; 2.1.1 QoS Metrics; 2.1.2 QoD Metrics; 2.2 Quality-Aware Scheduling in Data Management System; 2.2.1 Quality-Aware Scheduling in RTDBMS; 2.2.2 Quality-Aware Scheduling in DSMS; 2.2.3 Quality-Aware Scheduling in RDBMS; 2.2.4 Quality-Aware Scheduling in Key-Value Stores; 2.3 Summary; References; 3 Problem Overview

3.1 Background Knowledge3.1.1 Data Organization; 3.1.2 Data Replication and Consistency; 3.1.3 User Queries; 3.1.4 System Updates: State-Transfer Versus Operation-Transfer; 3.2 Problem Statement; 3.2.1 QoS Penalty; 3.2.2 QoD Penalty; 3.2.3 Combined Penalty; 3.3 Summary; References; 4 Scheduling for State-Transfer Updates; 4.1 On-Demand (OD) Mechanism; 4.1.1 WSJF-OD; 4.2 Hybrid On-Demand (HOD) Mechanism; 4.2.1 WSJF-HOD; 4.3 Freshness/Tardiness (FIT) Mechanism; 4.3.1 WSJF-FIT; 4.4 Adaptive Freshness/Tardiness (AFIT) Mechanism; 4.4.1 Query Routing; 4.4.2 Query Selection; 4.4.3 WSJF-AFIT

4.5 Popularity-Aware Mechanism4.5.1 Populairty-Aware WSJF-OD; 4.5.2 Populairty-Aware WSJF-HOD; 4.5.3 Popularity-Aware WSJF-FIT; 4.5.4 Popularity-Aware WSJF-AFIT; 4.6 Experimental Study; 4.6.1 Baseline Policies; 4.6.2 Parameter Setting; 4.6.3 Impact of Query Arrival Rate; 4.6.4 Impact of Update Cost; 4.6.5 Impact of Different QoS and QoD Preferences; 4.6.6 Impact of Popularity; 4.7 Summary; References; 5 Scheduling for Operation-Transfer Updates; 5.1 Hybrid On-Demand (HOD) Mechanism; 5.1.1 WSJF-HOD; 5.2 Freshness/Tardiness (FIT) Mechanism; 5.2.1 WSJF-FIT; 5.3 Popularity-Aware Mechanism

5.3.1 Popularity-Aware WSJF-HOD5.3.2 Popularity-Aware WSJF-FIT; 5.4 Experimental Study; 5.4.1 Parameter Setting; 5.4.2 Impact of Update Arrival Rate; 5.4.3 Impact of Popularity and Approximation; 5.5 Summary; References; 6 AQUAS: A Quality-Aware Scheduler; 6.1 System Overview; 6.1.1 System Goals; 6.1.2 System Design; 6.2 System Performance; 6.2.1 Benchmark; 6.2.2 Evaluation Result; 6.3 A Demonstration on MicroBlogging Application; 6.3.1 Timeline Queries in AQUAS; 6.3.2 A Case Study; 6.4 Summary; References; 7 Conclusion and Future Work; 7.1 Conclusion; 7.2 Future Work; References

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