Middleware alternatives for storm surge predictions in Windows Azure

Chandrasekar, Kavitha; Pathirage, Milinda; Wijeratne, Saminda; Mattocks, Craig; Plale, Beth

doi:10.1145/2287036.2287040

Cited by 4 publications

(2 citation statements)

References 13 publications

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“…For example, the Climate and Earth science project SLOSH [67] studies the efficiency of several middleware alternatives for storm surge predictions in Windows Azure. The Life science project CloudBLAST [4] uses MapReduce programming model to parallelize and speedup its programs, in order to provide distributed services for bioinformatics applications.…”

Section: Observation 6: Utilizing Vs Advancing Cloud Computingmentioning

confidence: 99%

A Taxonomy and Survey on eScience as a Service in the Cloud

Zhou,

He,

Ibrahim

2014

Preprint

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Cloud computing has recently evolved as a popular computing infrastructure for many applications. Scientific computing, which was mainly hosted in private clusters and grids, has started to migrate development and deployment to the public cloud environment. eScience as a service becomes an emerging and promising direction for science computing. We review recent efforts in developing and deploying scientific computing applications in the cloud. In particular, we introduce a taxonomy specifically designed for scientific computing in the cloud, and further review the taxonomy with four major kinds of science applications, including life sciences, physics sciences, social and humanities sciences, and climate and earth sciences. Our major finding is that, despite existing efforts in developing cloud-based eScience, eScience still has a long way to go to fully unlock the power of cloud computing paradigm. Therefore, we present the challenges and opportunities in the future development of cloud-based eScience services, and call for collaborations and innovations from both the scientific and computer system communities to address those challenges.

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Section: Observation 6: Utilizing Vs Advancing Cloud Computingmentioning

confidence: 99%

A Taxonomy and Survey on eScience as a Service in the Cloud

Zhou,

He,

Ibrahim

2014

Preprint

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“…Forecast information systems are fundamental components of emergency response systems. They are now emerging as operational tools for the management of harbours and marine resources (Daniel et al 2004;Baptista 2006;Anselmi-Molina et al 2012;Chandrasekar et al 2012;Wernera et al 2013), by providing precise and timely predictions on water conditions. Forecast systems integrate remote monitoring networks, HPC resources (due to demanding computation processes), either for short-term forecasting or resulting data processing, and web-based information systems to support management decisions (Baptista et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Operational forecast framework applied to extreme sea levels at regional and local scales

Fortunato

Oliveira

Rogeiro

et al. 2016

Journal of Operational Oceanography

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The design, implementation and demonstration of a novel and generic computational forecast framework for multi-scale prediction of extreme sea levels and associated flooding is presented. Denoted Water Information Forecast Framework (WIFF), it integrates process-based models for waves, tides and surges from regional to local scales, predicting the flooding of coastal areas, and supporting the routine and emergency management of coastal resources. WIFF manages the simulations and the real-time monitoring data, archives the data and makes the information available through a WebGIS that targets users with distinct access privileges. Additionally, the web component of WIFF adapts automatically and transparently to any device. WIFF also provides ways to assess the model accuracy and generates tailored products based on model results and observations. WIFF is demonstrated in the prediction of extreme water levels in the Portuguese coast, simulating processes at different scales: at basin scales, waves are simulated in the North Atlantic and in the Portuguese shelf, and sea levels due to tides and atmospheric forcings are simulated in the Northeast Atlantic; at estuarine scales, high-resolution, fully coupled wave/circulation predictions are performed in the Tagus estuary to account for wave-current interactions. User-oriented georeferenced products are generated, including automatic model/ data comparisons, targeting the needs of civil protection agents and combining for the first time an agile, service-oriented platform with high-resolution, process-rich predictions of the Tagus dynamics.

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