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

doi:10.1007/978-3-319-06859-6_30

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 proceeding › Conference contribution › peer-review

8 Citations (Scopus)

Abstract

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 language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Editors	A R Lomuscio, S Nepal, F Patrizi, B Benatallah and I BrandiÄ‡
Place of Publication	Switzerland
Publisher	Springer International Publishing
Pages	339-351pp
Edition	Peer reviewed
ISBN (Print)	9783319068596
DOIs	https://doi.org/10.1007/978-3-319-06859-6_30
Publication status	Published - 2014
Event	International Conference on Service-Oriented Computing, ICSOC 2013 - Berlin, Germany, Germany Duration: 1 Jan 2014 → …

Conference

Conference	International Conference on Service-Oriented Computing, ICSOC 2013
Country/Territory	Germany
Period	1/01/14 → …
Other	December 2-5 2013

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10.1007/978-3-319-06859-6_30

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Chen, S., Bednarz, T. P., Szul, P., Wang, D., Arzhaeva, Y., Burdett, N., Khassapov, A., Zic, J., Nepal, S., Gurevey, T., & Taylor, J. (2014). Galaxy + Hadoop: Toward a Collaborative and Scalable Image Processing Toolbox in Cloud. In A. R. L. S. N. F. P. B. B. A. I. B. (Ed.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Peer reviewed ed., pp. 339-351pp). Springer International Publishing. https://doi.org/10.1007/978-3-319-06859-6_30

Chen, Shiping ; Bednarz, Tomasz P. ; Szul, Piotr et al. / Galaxy + Hadoop: Toward a Collaborative and Scalable Image Processing Toolbox in Cloud. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). editor / A R Lomuscio, S Nepal, F Patrizi, B Benatallah and I BrandiÄ‡. Peer reviewed. ed. Switzerland : Springer International Publishing, 2014. pp. 339-351pp

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title = "Galaxy + Hadoop: Toward a Collaborative and Scalable Image Processing Toolbox in Cloud",

abstract = "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.",

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

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doi = "10.1007/978-3-319-06859-6_30",

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booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer International Publishing",

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Chen, S, Bednarz, TP, Szul, P, Wang, D, Arzhaeva, Y, Burdett, N, Khassapov, A, Zic, J, Nepal, S, Gurevey, T & Taylor, J 2014, Galaxy + Hadoop: Toward a Collaborative and Scalable Image Processing Toolbox in Cloud. in ARLSNFPBBAIB (ed.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Peer reviewed edn, Springer International Publishing, Switzerland, pp. 339-351pp, International Conference on Service-Oriented Computing, ICSOC 2013, Germany, 1/01/14. https://doi.org/10.1007/978-3-319-06859-6_30

Galaxy + Hadoop: Toward a Collaborative and Scalable Image Processing Toolbox in Cloud. / Chen, Shiping; Bednarz, Tomasz P.; Szul, Piotr et al.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). ed. / A R Lomuscio, S Nepal, F Patrizi, B Benatallah and I BrandiÄ‡. Peer reviewed. ed. Switzerland: Springer International Publishing, 2014. p. 339-351pp.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Arzhaeva, Yulia

AU - Burdett, Neil

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AU - Zic, John

AU - Nepal, Surya

AU - Gurevey, Tim

AU - Taylor, John

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AB - 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.

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Chen S, Bednarz TP, Szul P, Wang D, Arzhaeva Y, Burdett N et al. Galaxy + Hadoop: Toward a Collaborative and Scalable Image Processing Toolbox in Cloud. In ARLSNFPBBAIB, editor, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Peer reviewed ed. Switzerland: Springer International Publishing. 2014. p. 339-351pp doi: 10.1007/978-3-319-06859-6_30

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

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