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HotCDP 2012 Accepted Paper

April 29th, 2012

The Brown Data Management Research Group has the following paper in HotCDP 2012 from the C-MR Project:

  • Managing Parallelism for Stream Processing in the Cloud
       Nathan Backman, Rodrigo Fonseca, Ugur Cetintemel

    We present a framework that parallelizes and schedules workflows of stream operators, in real-time, to meet latency objectives. It supports data- and task-parallel processing of all workflow operators, by all computing nodes, while maintaining the ordering properties of sorted data streams. We show that a latency-oriented operator scheduling policy coupled with the diversification of computing node responsibilities encourages parallelism models that achieve end-to-end latency-minimization goals. We demonstrate the effectiveness of our framework with preliminary experimental results using a variety of real-world applications on heterogeneous clusters.