{"title":"Accurate weather forecasting through locality based collaborative computing","authors":"Bård Fjukstad, J. Bjørndalen, Otto J. Anshus","doi":"10.4108/ICST.COLLABORATECOM.2013.254178","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":222111,"journal":{"name":"9th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","volume":"151 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"9th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4108/ICST.COLLABORATECOM.2013.254178","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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.