A. Zahran, Jason J. Quinlan, Darijo Raca, C. Sreenan, Emir Halepovic, R. Sinha, R. Jana, V. Gopalakrishnan
{"title":"OSCAR:针对移动网络优化的失速谨慎自适应比特率流算法","authors":"A. Zahran, Jason J. Quinlan, Darijo Raca, C. Sreenan, Emir Halepovic, R. Sinha, R. Jana, V. Gopalakrishnan","doi":"10.1145/2910018.2910655","DOIUrl":null,"url":null,"abstract":"The design of an adaptive video client for mobile users is challenged by the frequent changes in operating conditions. Such conditions present a seemingly insurmountable challenge to adaptation algorithms, which may fail to find a balance between video rate, stalls, and rate-switching. In an effort to achieve the ideal balance, we design OSCAR, a novel adaptive streaming algorithm whose adaptation decisions are optimized to avoid stalls while maintaining high video quality. Our performance evaluation, using real video and channel traces from both 3G and 4G networks, shows that OSCAR achieves the highest percentage of stall-free sessions while maintaining a high quality video in comparison to the state-of-the-art algorithms.","PeriodicalId":165789,"journal":{"name":"MoVid '16","volume":"42 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"OSCAR: an optimized stall-cautious adaptive bitrate streaming algorithm for mobile networks\",\"authors\":\"A. Zahran, Jason J. Quinlan, Darijo Raca, C. Sreenan, Emir Halepovic, R. Sinha, R. Jana, V. Gopalakrishnan\",\"doi\":\"10.1145/2910018.2910655\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The design of an adaptive video client for mobile users is challenged by the frequent changes in operating conditions. Such conditions present a seemingly insurmountable challenge to adaptation algorithms, which may fail to find a balance between video rate, stalls, and rate-switching. In an effort to achieve the ideal balance, we design OSCAR, a novel adaptive streaming algorithm whose adaptation decisions are optimized to avoid stalls while maintaining high video quality. Our performance evaluation, using real video and channel traces from both 3G and 4G networks, shows that OSCAR achieves the highest percentage of stall-free sessions while maintaining a high quality video in comparison to the state-of-the-art algorithms.\",\"PeriodicalId\":165789,\"journal\":{\"name\":\"MoVid '16\",\"volume\":\"42 4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-05-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"MoVid '16\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2910018.2910655\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"MoVid '16","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2910018.2910655","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
OSCAR: an optimized stall-cautious adaptive bitrate streaming algorithm for mobile networks
The design of an adaptive video client for mobile users is challenged by the frequent changes in operating conditions. Such conditions present a seemingly insurmountable challenge to adaptation algorithms, which may fail to find a balance between video rate, stalls, and rate-switching. In an effort to achieve the ideal balance, we design OSCAR, a novel adaptive streaming algorithm whose adaptation decisions are optimized to avoid stalls while maintaining high video quality. Our performance evaluation, using real video and channel traces from both 3G and 4G networks, shows that OSCAR achieves the highest percentage of stall-free sessions while maintaining a high quality video in comparison to the state-of-the-art algorithms.