{"title":"C2: Procuring uncertain freelancers for interactive live video transcoding","authors":"Yifei Zhu, Jiangchuan Liu","doi":"10.1109/IWQoS.2017.7969179","DOIUrl":null,"url":null,"abstract":"Live video contents in crowdsourced live streaming services are transcoded into multiple quality versions to better service viewers with different network and device configurations. Cloud computing becomes a natural choice to handle this transcoding service due to its elasticity and significant computational power. However, given the huge concurrent channel numbers in this crowdsourced live streaming service, even the cloud becomes significantly expensive for providing transcoding services to the whole community. In this poster, after observing that abundant computational resources reside in end viewers, we propose a Cloud-Crowd collaborative system, C2, which incentivizes idle end-viewers to join with the cloud to do video transcoding. Specifically, we propose an auction mechanism to carefully select stable viewers and determine the proper payment for them. Desirable economic properties, like incentive compatibility, can be achieved in our mechanism. Large-scale trace-driven simulations further demonstrate the superiority of our mechanisms in cost reduction and service stability.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWQoS.2017.7969179","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
Live video contents in crowdsourced live streaming services are transcoded into multiple quality versions to better service viewers with different network and device configurations. Cloud computing becomes a natural choice to handle this transcoding service due to its elasticity and significant computational power. However, given the huge concurrent channel numbers in this crowdsourced live streaming service, even the cloud becomes significantly expensive for providing transcoding services to the whole community. In this poster, after observing that abundant computational resources reside in end viewers, we propose a Cloud-Crowd collaborative system, C2, which incentivizes idle end-viewers to join with the cloud to do video transcoding. Specifically, we propose an auction mechanism to carefully select stable viewers and determine the proper payment for them. Desirable economic properties, like incentive compatibility, can be achieved in our mechanism. Large-scale trace-driven simulations further demonstrate the superiority of our mechanisms in cost reduction and service stability.