Provided by: Australian Computer Society
Highly distributed data management platforms (e.g., PNUTS, Dynamo, Cassandra, and BigTable) are rapidly becoming the favorite choice for hosting modern web applications in the cloud. Among other features, these 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 performance and data freshness. In this paper, in addition to performance SLAs, the authors also perceive an application tolerance to data staleness as another requirement determining the end-user satisfaction and their goal is to strike a fine balance between both the Quality of Service (QoS) and Quality of Data (QoD) perceived by the end-user.