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

Autor:	Dadong Wang, Piotr Szul, John Taylor, John Zic, Neil Burdett, Shiping Chen, Tomasz Bednarz, Alex Khassapov, Surya Nepal, Tim Gurevey, Yulia Arzhaeva
Rok vydání:	2014
Předmět:	Collaborative software Workflow Software Computer architecture business.industry Computer science Scalability Real-time computing Image processing Cloud computing business Real image Toolbox
Zdroj:	Lecture Notes in Computer Science ISBN: 9783319068589 ICSOC Workshops
DOI:	10.1007/978-3-319-06859-6_30
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::a9391fdb416a71306f1ecf5cae14bdef https://doi.org/10.1007/978-3-319-06859-6_30 Zobrazit plný text záznamu