Scaling IIIF Image Tiling in the Cloud

dc.contributor.authorChen, Yinlinen
dc.contributor.authorGhosh, Soumiken
dc.contributor.authorJiang, Tingtingen
dc.contributor.authorTuttle, Jamesen
dc.date.accessioned2020-02-18T16:06:03Zen
dc.date.available2020-02-18T16:06:03Zen
dc.date.issued2020-02-17en
dc.description.abstractThe International Archive of Women in Architecture, established at Virginia Tech in 1985, collects books, biographical information, and published materials from nearly 40 countries that are divided into around 450 collections. In order to provide public access to these collections, we built an application using the IIIF APIs to pre-generate image tiles and manifests which are statically served in the AWS cloud. We established an automatic image processing pipeline using a suite of AWS services to implement microservices in Lambda and Docker. By doing so, we reduced the processing time for terabytes of images from weeks to days. In this article, we describe our serverless architecture design and implementations, elaborate the technical solution on integrating multiple AWS services with other techniques into the application, and describe our streamlined and scalable approach to handle extremely large image datasets. Finally, we show the significantly improved performance compared to traditional processing architectures along with a cost evaluation.en
dc.format.mimetypeapplication/pdfen
dc.identifier.issn1940-5758en
dc.identifier.issue47en
dc.identifier.urihttp://hdl.handle.net/10919/96923en
dc.identifier.urlhttps://journal.code4lib.org/articles/14933en
dc.language.isoenen
dc.rightsCreative Commons Attribution 3.0 United Statesen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/en
dc.titleScaling IIIF Image Tiling in the Clouden
dc.title.serialCode4Lib Journalen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.dcmitypeStillImageen

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