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dc.contributor.authorSubratie, Ken_US
dc.contributor.authorAditya, Sen_US
dc.contributor.authorFigueiredo, Ren_US
dc.contributor.authorCarey, Cayelan C.en_US
dc.contributor.authorHanson, Pen_US
dc.date.accessioned2016-10-19T20:03:37Z
dc.date.available2016-10-19T20:03:37Z
dc.identifier.urihttp://hdl.handle.net/10919/73296
dc.description.abstractThe GLEON Research And PRAGMA Lake Expedition -- GRAPLE -- is a collaborative effort between computer science and lake ecology researchers. It aims to improve our understanding and predictive capacity of the threats to the water quality of our freshwater resources, including climate change. This paper presents GRAPLEr, a distributed computing system used to address the modeling needs of GRAPLE researchers. GRAPLEr integrates and applies overlay virtual network, high-throughput computing, and Web service technologies in a novel way. First, its user-level IP-over-P2P (IPOP) overlay network allows compute and storage resources distributed across independently-administered institutions (including private and public clouds) to be aggregated into a common virtual network, despite the presence of firewalls and network address translators. Second, resources aggregated by the IPOP virtual network run unmodified high-throughput computing middleware (HTCondor) to enable large numbers of model simulations to be executed concurrently across the distributed computing resources. Third, a Web service interface allows end users to submit job requests to the system using client libraries that integrate with the R statistical computing environment. The paper presents the GRAPLEr architecture, describes its implementation and reports on its performance for batches of General Lake Model (GLM) simulations across three cloud infrastructures (University of Florida, CloudLab, and Microsoft Azure).en_US
dc.relation.urihttp://arxiv.org/abs/1509.08955v1en_US
dc.subjectcs.DCen_US
dc.subjectcs.DCen_US
dc.titleGRAPLEr: A Distributed Collaborative Environment for Lake Ecosystem Modeling that Integrates Overlay Networks, High-throughput Computing, and Web Servicesen_US
dc.typeArticle - Refereed
dc.description.notes8 pages, 7 figures. PRAGMA29en_US
pubs.organisational-group/Virginia Tech
pubs.organisational-group/Virginia Tech/All T&R Faculty
pubs.organisational-group/Virginia Tech/Science
pubs.organisational-group/Virginia Tech/Science/Biological Sciences
pubs.organisational-group/Virginia Tech/Science/COS T&R Faculty


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