Galaxy + Hadoop: Toward a Collaborative and Scalable Image Processing Toolbox in Cloud

Shiping Chen, Tomasz P. Bednarz, Piotr Szul, Dadong Wang, Yulia Arzhaeva, Neil Burdett, Alex Khassapov, John Zic, Surya Nepal, Tim Gurevey, John Taylor

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    8 Citations (Scopus)


    With emergence and adoption of cloud computing, cloud has become an effective collaboration platform for integrating various software tools to deliver as services. In this paper, we present a cloud-based image processing toolbox by integrating Galaxy, Hadoop and our proprietary image processing tools. This toolbox allows users to easily design and execute complex image processing tasks by sharing various advanced image processing tools and scalable cloud computation capacity. The paper provides the integration architecture and technical details about the whole system. In particular, we present our investigations to use Hadoop to handle massive image processing jobs in the system. A number of real image processing examples are used to demonstrate the usefulness and scalability of this class of data-intensive applications.
    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    EditorsA R Lomuscio, S Nepal, F Patrizi, B Benatallah and I Brandić
    Place of PublicationSwitzerland
    PublisherSpringer International Publishing
    EditionPeer reviewed
    ISBN (Print)9783319068596
    Publication statusPublished - 2014
    EventInternational Conference on Service-Oriented Computing, ICSOC 2013 - Berlin, Germany, Germany
    Duration: 1 Jan 2014 → …


    ConferenceInternational Conference on Service-Oriented Computing, ICSOC 2013
    Period1/01/14 → …
    OtherDecember 2-5 2013


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