{"title":"Steward: smart edge based joint QoE optimization for adaptive video streaming","authors":"Xiaoteng Ma, Qing Li, Jimeng Chai, Xi Xiao, Shutao Xia, Yong Jiang","doi":"10.1145/3304112.3325603","DOIUrl":"https://doi.org/10.1145/3304112.3325603","url":null,"abstract":"With the increase of HTTP-based adaptive video streaming over the Internet, multiple clients may compete for a shared bottleneck bandwidth, which brings some damage to the fairness and stability of Quality of Experience (QoE). This paper presents Steward, a system that enforces multi-client joint QoE optimization for bottleneck bandwidth sharing. Joint QoE optimization refers to improving QoE fairness among clients with various video devices and providing differentiated service for clients with different priorities. Steward deploys the adaptive bitrate (ABR) algorithm based on neural networks (NN) and reinforcement learning at the network edge. The ABR agent trains the NN model through experience and makes appropriate bitrate guidance for video chunks to be requested by clients sharing the same bottleneck bandwidth. We compare Steward with state-of-the-art algorithms under different network conditions. Compared with all considered algorithms and conditions, Steward reduces 30%~85% QoE unfairness under the premise of differentiated service.","PeriodicalId":368888,"journal":{"name":"Proceedings of the 29th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video","volume":"247 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128655122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Video processing with serverless computing: a measurement study","authors":"Miao Zhang, Yifei Zhu, Cong Zhang, Jiangchuan Liu","doi":"10.1145/3304112.3325608","DOIUrl":"https://doi.org/10.1145/3304112.3325608","url":null,"abstract":"The growing demand for video processing and the advantages in scalability and cost reduction brought by the emerging serverless computing have attracted significant attention in serverless computing powered video processing. However, how to implement and configure serverless functions to optimize the performance and cost of video processing applications remains unclear. In this paper, we explore the configuration and implementation schemes of typical video processing functions deployed to the serverless platforms and quantify their influence on the execution duration and monetary cost from a developer's perspective. Our measurement reveals that memory configuration is non-trivial. Dynamic profiling of workloads is necessary to find the best memory configuration. Moreover, compared with calling external video processing APIs, implementing these services locally in serverless functions can be competitive. We also find that the performance of video processing applications could be affected by the underlying infrastructure. Our work provides guidelines for further function-level optimization and complements the existing measurement studies for both serverless computing and video processing.","PeriodicalId":368888,"journal":{"name":"Proceedings of the 29th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114665291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Proceedings of the 29th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video","authors":"","doi":"10.1145/3304112","DOIUrl":"https://doi.org/10.1145/3304112","url":null,"abstract":"","PeriodicalId":368888,"journal":{"name":"Proceedings of the 29th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128707641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}