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Issue No.04 - July-Aug. (2013 vol.15)
pp: 30-37
D. K. Krishnappa , Univ. of Massachusetts, Amherst, MA, USA
D. Irwin , Univ. of Massachusetts, Amherst, MA, USA
E. Lyons , Univ. of Massachusetts, Amherst, MA, USA
M. Zink , Univ. of Massachusetts, Amherst, MA, USA
CloudCast provides clients with personalized short-term weather forecasts based on their current location using cloud services, generating accurate forecasts tens of minutes in the future for small areas. Results show that it takes less than 2 minutes from the start of data sampling to deliver a 15-minute forecast to a client.
Cloud computing, Performance evaluation, Scientific computing, Online services, Electronic commerce,performance analysis, Nowcasting, scientific computing, cloud computing, Amazon EC2, measurements
D. K. Krishnappa, D. Irwin, E. Lyons, M. Zink, "CloudCast: Cloud Computing for Short-Term Weather Forecasts", Computing in Science & Engineering, vol.15, no. 4, pp. 30-37, July-Aug. 2013, doi:10.1109/MCSE.2013.43
1. E. Ruzanski, Y. Wang, and V. Chandrasekar, “Development of a Real-Time Dynamic and Adaptive Nowcasting System,” Proc. Interactive Information and Processing Systems for Meteorology, Oceanography, and Hydrology, 2009; paper_149633.htm.
2. E. Ruzanski, V. Chandrasekar, and Y. Wang, “The CASA Nowcasting System,” J. Atmospheric and Oceanic Technology, 2011.
3. M. Yuen, “GENI in the Cloud,” master's thesis, Dept. of Computer Science, Univ. of Victoria, 2010.
4. A.C. Bavier et al., “Transcloud—Design Considerations for a High-Performance Cloud Architecture Across Multiple Administrative Domains,” Proc. 1st Int'l Conf. Cloud Computing and Services Science, Springer, 2011; .
5. M. Zink et al., “Closed-Loop Architecture for Distributed Collaborative Adaptive Sensing: Meteorogolical Command & Control,” Int'l J. Sensor Networks, vol. 7, nos. 1–2, 2010, pp. 4-18.
6. B. Chun et al., “PlanetLab: An Overlay Testbed for Broadcoverage Services,” SIGCOMM Computer Comm. Rev., vol. 33, no. 3, 2003, pp. 3-12.
7. D. Nurmi et al., “The Eucalyptus Open-Source Cloud-Computing System,” Proc. 2009 9th IEEE/ACM Int'l Symp. Cluster Computing and the Grid, IEEE CS, 2009, pp. 124-131.
8. K.E. Kelleher et al., “Project CRAFT: A Real-Time Delivery System for NEXRAD Level II Data via the Internet,” Bull. Am. Meteorological Soc., vol. 88, 2007, pp. 1045-1057;
9. D. McLaughlin et al., “Short-Wavelength Technology and the Potential for Distributed Networks of Small Radar Systems,” Bull. Am. Meteorological Soc., vol. 90, 2009, pp. 1797-1817;
10. D.K. Krishnappa et al., “Network Capabilities of Cloud Services for a Real Time Scientific Application,” Proc. Local Computer Networks, IEEE, 2012, pp. 487-495.
11. D.K. Krishnappa et al., “CloudCast: Cloud Computing for Short-Term Mobile Weather Forecasts,” Proc. Int'l Performance, Computing, and Comm. Conf., IEEE, 2012, pp. 61-70.
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