Distributed and Parallel Databases

, Volume 32, Issue 4, pp 535–581 | Cite as

Quality-aware schedulers for weak consistency key-value data stores

  • Chen Xu
  • Mohamed A. Sharaf
  • Xiaofang Zhou
  • Aoying ZhouEmail author


Highly distributed NoSQL key-value data stores are rapidly becoming the favorite choice for hosting modern web applications. Such platforms rely on data partitioning, replication and relaxed consistency to achieve high levels of performance and scalability. However, these design choices often exhibit a trade-off between latency (i.e., Quality of Service (QoS)) and consistency (i.e., Quality of Data (QoD)). In this work, in addition to latency-based SLAs, we also adopt the application tolerance to data staleness as another requirement determining the end-user satisfaction and our goal is to strike a fine balance between both the QoS and QoD provided to the end-user. Towards achieving that goal, we propose a suite of quality-aware schedulers for efficiently allocating the necessary computational resources between the foreground user-queries and the background system-updates at data store nodes. This suite of schedulers features our proposed Freshness/Tardiness (FIT) mechanism, which introduces a novel selective approach for scheduling the execution of queries and updates. Our experimental results show that FIT provides significant improvements in balancing the trade-off between QoS and QoD under both the state-transfer and operation-transfer update propagation models employed in current key-value data stores.


NoSQL Key-value data stores Distributed database Scheduling Consistency SLA FLA Quality of data Quality of service 



The authors would like to thank the anonymous reviewers for their valuable comments and suggestions. This work is partially supported by the Shanghai Knowledge Services Platform for Trustworthy Internet of Things (ZF1213), grants from Australian Research Council (DP110102777, DP120102829), MoST of China (2010CB731402, 2012AA011001, 2012AA011003) and NSFC grants (61021004, 60925008).


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Chen Xu
    • 1
  • Mohamed A. Sharaf
    • 2
  • Xiaofang Zhou
    • 2
  • Aoying Zhou
    • 1
    Email author
  1. 1.Software Engineering InstituteEast China Normal UniversityShanghaiChina
  2. 2.School of Information Technology & Electrical EngineeringThe University of QueenslandBrisbaneAustralia

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