{"title":"移动视频流中的数据浪费","authors":"Guanghui Zhang, Jack Y. B. Lee","doi":"10.1109/WCNC.2018.8376959","DOIUrl":null,"url":null,"abstract":"Mobile video streaming is now ubiquitous among mobile users. This work investigated an often-neglected problem — data wastage where downloaded video data were not played back due to user early departure. Empirical measurements showed that data wastage is significant, e.g., around 20% of data downloaded were in fact wasted. Moreover, substantial data wastage exists not only in current commercial streaming platforms, but also in advanced adaptive streaming algorithms proposed in the literature. This work developed a new Post-Streaming Wastage Analysis (PSWA) framework to tackle the problem by converting existing adaptive streaming algorithms into wastage-aware. PSWA enables the service provider to control the tradeoff between data wastage and streaming quality-of-experience (QoE). Most remarkably, PSWA can achieve significant data wastage reduction (e.g., over 70%) even without negatively impacting QoE. PSWA can be applied to existing or future adaptive streaming algorithms and thus offers a practical solution to data wastage in current and future streaming services.","PeriodicalId":360054,"journal":{"name":"2018 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"On data wastage in mobile video streaming\",\"authors\":\"Guanghui Zhang, Jack Y. B. Lee\",\"doi\":\"10.1109/WCNC.2018.8376959\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mobile video streaming is now ubiquitous among mobile users. This work investigated an often-neglected problem — data wastage where downloaded video data were not played back due to user early departure. Empirical measurements showed that data wastage is significant, e.g., around 20% of data downloaded were in fact wasted. Moreover, substantial data wastage exists not only in current commercial streaming platforms, but also in advanced adaptive streaming algorithms proposed in the literature. This work developed a new Post-Streaming Wastage Analysis (PSWA) framework to tackle the problem by converting existing adaptive streaming algorithms into wastage-aware. PSWA enables the service provider to control the tradeoff between data wastage and streaming quality-of-experience (QoE). Most remarkably, PSWA can achieve significant data wastage reduction (e.g., over 70%) even without negatively impacting QoE. PSWA can be applied to existing or future adaptive streaming algorithms and thus offers a practical solution to data wastage in current and future streaming services.\",\"PeriodicalId\":360054,\"journal\":{\"name\":\"2018 IEEE Wireless Communications and Networking Conference (WCNC)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Wireless Communications and Networking Conference (WCNC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCNC.2018.8376959\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Wireless Communications and Networking Conference (WCNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCNC.2018.8376959","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mobile video streaming is now ubiquitous among mobile users. This work investigated an often-neglected problem — data wastage where downloaded video data were not played back due to user early departure. Empirical measurements showed that data wastage is significant, e.g., around 20% of data downloaded were in fact wasted. Moreover, substantial data wastage exists not only in current commercial streaming platforms, but also in advanced adaptive streaming algorithms proposed in the literature. This work developed a new Post-Streaming Wastage Analysis (PSWA) framework to tackle the problem by converting existing adaptive streaming algorithms into wastage-aware. PSWA enables the service provider to control the tradeoff between data wastage and streaming quality-of-experience (QoE). Most remarkably, PSWA can achieve significant data wastage reduction (e.g., over 70%) even without negatively impacting QoE. PSWA can be applied to existing or future adaptive streaming algorithms and thus offers a practical solution to data wastage in current and future streaming services.