{"title":"网络气象服务中的多元资源性能预测","authors":"M. Swany, R. Wolski","doi":"10.1109/SC.2002.10039","DOIUrl":null,"url":null,"abstract":"This paper describes a new technique in the Network Weather Service for producing multi-variate forecasts. The new technique uses the NWS’s univariate forecasters and emprically gathered Cumulative Distribution Functions (CDFs) to make predictions from correlated measurement streams. Experimental results are shown in which throughput is predicted for long TCP/IP transfers from short NWS network probes.","PeriodicalId":302800,"journal":{"name":"ACM/IEEE SC 2002 Conference (SC'02)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"104","resultStr":"{\"title\":\"Multivariate Resource Performance Forecasting in the Network Weather Service\",\"authors\":\"M. Swany, R. Wolski\",\"doi\":\"10.1109/SC.2002.10039\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes a new technique in the Network Weather Service for producing multi-variate forecasts. The new technique uses the NWS’s univariate forecasters and emprically gathered Cumulative Distribution Functions (CDFs) to make predictions from correlated measurement streams. Experimental results are shown in which throughput is predicted for long TCP/IP transfers from short NWS network probes.\",\"PeriodicalId\":302800,\"journal\":{\"name\":\"ACM/IEEE SC 2002 Conference (SC'02)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"104\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM/IEEE SC 2002 Conference (SC'02)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SC.2002.10039\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM/IEEE SC 2002 Conference (SC'02)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SC.2002.10039","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multivariate Resource Performance Forecasting in the Network Weather Service
This paper describes a new technique in the Network Weather Service for producing multi-variate forecasts. The new technique uses the NWS’s univariate forecasters and emprically gathered Cumulative Distribution Functions (CDFs) to make predictions from correlated measurement streams. Experimental results are shown in which throughput is predicted for long TCP/IP transfers from short NWS network probes.