YongChul Kwon

  1. Astronomy in the Cloud: Using MapReduce for Image Coaddition.

    Authors: YongChul Kwon, Keith Wiley, Andrew Connolly, Jeff Gardner, Simon Krughof, Magdalena Balazinska, Bill Howe, YingYi Bu
    Subjects: and Cluster Computing, Distributed, Parallel
    Abstract

    In the coming decade, astronomical surveys of the sky will generate tens of
    terabytes of images and detect hundreds of millions of sources every night. The
    study of these sources will involve computation challenges such as anomaly
    detection and classification, and moving object tracking. Since such studies
    benefit from the highest quality data, methods such as image coaddition
    (stacking) will be a critical preprocessing step prior to scientific
    investigation.

  2. A Case for A Collaborative Query Management System.

    Authors: Nodira Khoussainova, Magda Balazinska, Wolfgang Gatterbauer, YongChul Kwon, Dan Suciu
    Subjects: Databases
    Abstract

    Over the past 40 years, database management systems (DBMSs) have evolved to
    provide a sophisticated variety of data management capabilities. At the same
    time, tools for managing queries over the data have remained relatively
    primitive. One reason for this is that queries are typically issued through
    applications. They are thus debugged once and re-used repeatedly. This mode of
    interaction, however, is changing. As scientists (and others) store and share
    increasingly large volumes of data in data centers, they need the ability to
    analyze the data by issuing exploratory queries.

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