Scalable Distributed Image Transcoding Using Python-WorkQueue

Simple item page
dc.contributor.advisorBui, Peter
dc.contributor.authorWestphal, Jeffrey
dc.date.accessioned2014-01-17T16:07:30Z
dc.date.available2014-01-17T16:07:30Z
dc.date.issued2013-05
dc.descriptionColor poster with text, charts, graphs, and tables.en
dc.description.abstractTranscoding large amounts of digital media from one format to another is a common data intensive workflow. The purpose of this study was to present a scalable image transcoding system based on Python-WorkQueue that significantly reduces the amount of time required to convert images from one format to another by mapping transcoding tasks across a distributed pool of remote workers.en
dc.description.sponsorshipUniversity of Wisconsin--Eau Claire Office of Research and Sponsored Programs.en
dc.identifier.urihttp://digital.library.wisc.edu/1793/67828
dc.language.isoen_USen
dc.relation.ispartofseriesUSGZE AS589en
dc.subjectTranscodingen
dc.subjectDigital mediaen
dc.subjectPython-WorkQueueen
dc.subjectPostersen
dc.titleScalable Distributed Image Transcoding Using Python-WorkQueueen
dc.typePresentationen

Files

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
WestphalSpr2013.pdf
Size:
1.06 MB
Format:
Adobe Portable Document Format
Download

License bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
2.03 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Student Research Day