Cise Midoglu, M. Avelino, Shri Hari Gopalakrishnan, S. Pham, P. Halvorsen
{"title":"Multimedia streaming analytics: quo vadis?","authors":"Cise Midoglu, M. Avelino, Shri Hari Gopalakrishnan, S. Pham, P. Halvorsen","doi":"10.1145/3510450.3517321","DOIUrl":null,"url":null,"abstract":"In today's complex OTT multimedia streaming ecosystem, the task of ensuring the best streaming experience to end-users requires extensive monitoring, and such monitoring information is relevant to various stakeholders including content providers, CDN providers, network operators, device vendors, developers, and researchers. Streaming analytics solutions address this need by aggregating performance information across streaming sessions, to be presented in ways that help improve the end-to-end delivery. In this paper, we provide an analysis of the state of the art in commercial streaming analytics solutions. We consider five products as representatives, and identify potential improvements with respect to terminology, QoE representation, standardization and interoperability, and collaboration with academia and the developer community.","PeriodicalId":122386,"journal":{"name":"Proceedings of the 1st Mile-High Video Conference","volume":"288 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 1st Mile-High Video Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3510450.3517321","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
In today's complex OTT multimedia streaming ecosystem, the task of ensuring the best streaming experience to end-users requires extensive monitoring, and such monitoring information is relevant to various stakeholders including content providers, CDN providers, network operators, device vendors, developers, and researchers. Streaming analytics solutions address this need by aggregating performance information across streaming sessions, to be presented in ways that help improve the end-to-end delivery. In this paper, we provide an analysis of the state of the art in commercial streaming analytics solutions. We consider five products as representatives, and identify potential improvements with respect to terminology, QoE representation, standardization and interoperability, and collaboration with academia and the developer community.