Accurate weather forecasting through locality based collaborative computing

The Collaborative Symbiotic Weather Forecasting (CSWF) system lets a user compute a short time, high-resolution forecast for a small region around the user, in a few minutes, on-demand, on a PC. A collaborated forecast giving better uncertainty estimation is then created using forecasts from other users in the same general region. A collaborated forecast can be visualized on a range of devices and in a range of styles, typically as a composite of the individual forecasts. CSWF assumes locality between forecasts, regions, and PCs. Forecasts for a region are computed by and stored on PCs located within the region. To locate forecasts, CSWF simply scans specific ports on public IP addresses in the local area. Scanning is robust because it avoids maintaining state about others and fast because the number of computers is low and only a few forecasts are needed.

[1]  Murat Ali Bayir,et al.  Crowd-sourced sensing and collaboration using twitter , 2010, 2010 IEEE International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM).

[2]  Jan Gäbler,et al.  Mobile XMPP and cloud service collaboration: An alliance for flexible disaster management , 2011, 7th International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom).

[3]  C. Ziehmann.  Comparison of a single-model EPS with a multi-model ensemble consisting of a few operational models , 2000 .

[4]  Christian Grothoff,et al.  Autonomous NAT Traversal , 2010, 2010 IEEE Tenth International Conference on Peer-to-Peer Computing (P2P).

[5]  Roy Fielding,et al.  Architectural Styles and the Design of Network-based Software Architectures"; Doctoral dissertation , 2000 .

[6]  John Markus Bjørndalen,et al.  Embarrassingly Distributed Computing for Symbiotic Weather Forecasts , 2013, ICCS.

[7]  Ozgur Ozturk.  Introduction to XMPP protocol and developing online collaboration applications using open source software and libraries , 2010, 2010 International Symposium on Collaborative Technologies and Systems.

[8]  Richard Han,et al.  Proceedings of the 1st ACM Workshop on Mobile Cloud Computing & Services: Social Networks and Beyond , 2010, Mobisys 2010.

[9]  Moncho Gómez-Gesteira,et al.  A sensitivity study of the WRF model in wind simulation for an area of high wind energy , 2012, Environ. Model. Softw..

[10]  Keith M. Hines,et al.  Development and Testing of Polar Weather Research and Forecasting (WRF) Model. Part I: Greenland Ice Sheet Meteorology* , 2008 .

[11]  John Markus Bjørndalen,et al.  De-centralizing the VNC Model for Improved Performance on Wall-Sized, High-Resolution Tiled Displays , 2007 .

[12]  Celeste Saulo,et al.  WRF Model Sensitivity to Choice of Parameterization over South America: Validation against Surface Variables , 2010 .

[13]  Ronny Klauck,et al.  Chatty things - Making the Internet of Things readily usable for the masses with XMPP , 2012, 8th International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom).