AQUAS: A quality-aware scheduler for NoSQL data stores

Chen Xu, Fan Xia, Mohamed A. Sharaf, Minqi Zhou, Aoying Zhou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)


NoSQL key-value data stores provide an attractive solution for big data management. With the help of data partitioning and replication, those data stores achieve higher levels of availability, scalability and reliability. Such design choices typically exhibit a tradeoff in which data freshness is sacrificed in favor of reduced access latency. At the replica-level, this tradeoff is primarily shaped by the resource allocation strategies deployed for managing the processing of user queries and replica updates. In this demonstration, we showcase AQUAS: a quality-aware scheduler for Cassandra, which allows application developers to specify requirements on quality of service (QoS) and quality of data (QoD). AQUAS efficiently allocates the available replica resources to execute the incoming read/write tasks so that to minimize the penalties incurred by violating those requirements. We demonstrate AQUAS based on our implementation of a microblogging system.

Original languageEnglish
Title of host publication2014 IEEE 30th International Conference on Data Engineering, ICDE 2014
PublisherIEEE Computer Society
Number of pages4
ISBN (Print)9781479925544
Publication statusPublished - 2014
Externally publishedYes
Event30th IEEE International Conference on Data Engineering, ICDE 2014 - Chicago, IL, United States
Duration: Mar 31 2014Apr 4 2014

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627


Conference30th IEEE International Conference on Data Engineering, ICDE 2014
Country/TerritoryUnited States
CityChicago, IL

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems


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