{"title":"大规模操作点播流与随机网络编码","authors":"Zimu Liu, Chuan Wu, Baochun Li, Shuqiao Zhao","doi":"10.1109/INFCOM.2010.5462030","DOIUrl":null,"url":null,"abstract":"Since the inception of network coding in information theory, we have witnessed a sharp increase of research interest in its applications in communications and networking, where the focus has been on more practical aspects. However, thus far, network coding has not been deployed in real-world commercial systems in operation at a large scale, and in a production setting. In this paper, we present the objectives, rationale, and design in the first production deployment of random network coding, where it has been used in the past year as the cornerstone of a large-scale production on-demand streaming system, operated by UUSee Inc., delivering thousands of on-demand video channels to millions of unique visitors each month. To achieve a thorough understanding of the performance of network coding, we have collected 200 Gigabytes worth of real-world traces throughout the 17-day Summer Olympic Games in August 2008, and present our lessons learned after an in-depth trace-driven analysis.","PeriodicalId":259639,"journal":{"name":"2010 Proceedings IEEE INFOCOM","volume":"86 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"191","resultStr":"{\"title\":\"UUSee: Large-Scale Operational On-Demand Streaming with Random Network Coding\",\"authors\":\"Zimu Liu, Chuan Wu, Baochun Li, Shuqiao Zhao\",\"doi\":\"10.1109/INFCOM.2010.5462030\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Since the inception of network coding in information theory, we have witnessed a sharp increase of research interest in its applications in communications and networking, where the focus has been on more practical aspects. However, thus far, network coding has not been deployed in real-world commercial systems in operation at a large scale, and in a production setting. In this paper, we present the objectives, rationale, and design in the first production deployment of random network coding, where it has been used in the past year as the cornerstone of a large-scale production on-demand streaming system, operated by UUSee Inc., delivering thousands of on-demand video channels to millions of unique visitors each month. To achieve a thorough understanding of the performance of network coding, we have collected 200 Gigabytes worth of real-world traces throughout the 17-day Summer Olympic Games in August 2008, and present our lessons learned after an in-depth trace-driven analysis.\",\"PeriodicalId\":259639,\"journal\":{\"name\":\"2010 Proceedings IEEE INFOCOM\",\"volume\":\"86 \",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-03-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"191\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Proceedings IEEE INFOCOM\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INFCOM.2010.5462030\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Proceedings IEEE INFOCOM","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INFCOM.2010.5462030","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
UUSee: Large-Scale Operational On-Demand Streaming with Random Network Coding
Since the inception of network coding in information theory, we have witnessed a sharp increase of research interest in its applications in communications and networking, where the focus has been on more practical aspects. However, thus far, network coding has not been deployed in real-world commercial systems in operation at a large scale, and in a production setting. In this paper, we present the objectives, rationale, and design in the first production deployment of random network coding, where it has been used in the past year as the cornerstone of a large-scale production on-demand streaming system, operated by UUSee Inc., delivering thousands of on-demand video channels to millions of unique visitors each month. To achieve a thorough understanding of the performance of network coding, we have collected 200 Gigabytes worth of real-world traces throughout the 17-day Summer Olympic Games in August 2008, and present our lessons learned after an in-depth trace-driven analysis.