{"title":"基于sdn的编解码器视频传输","authors":"Obinna Izima, R. Fréin, Ali Malik","doi":"10.21427/4VMV-G820","DOIUrl":null,"url":null,"abstract":"To guarantee quality of delivery for video streaming over software defined networks, efficient predictors and adaptive routing frameworks are required. We demonstrate an agent that predicts video quality of delivery metrics in a scalable way using a bespoke codec-aware learning model. We also demonstrate the integration of this agent with an adaptive framework for centrally controlled software-defined networks that re-configures network operational paths in response to the learning agent, ensuring that good quality of delivery of video is maintained during periods of congestion. The demo scenario highlights the feasibility, scalability and accuracy of the framework.","PeriodicalId":404815,"journal":{"name":"2021 IFIP/IEEE International Symposium on Integrated Network Management (IM)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Codec-Aware Video Delivery Over SDNs\",\"authors\":\"Obinna Izima, R. Fréin, Ali Malik\",\"doi\":\"10.21427/4VMV-G820\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To guarantee quality of delivery for video streaming over software defined networks, efficient predictors and adaptive routing frameworks are required. We demonstrate an agent that predicts video quality of delivery metrics in a scalable way using a bespoke codec-aware learning model. We also demonstrate the integration of this agent with an adaptive framework for centrally controlled software-defined networks that re-configures network operational paths in response to the learning agent, ensuring that good quality of delivery of video is maintained during periods of congestion. The demo scenario highlights the feasibility, scalability and accuracy of the framework.\",\"PeriodicalId\":404815,\"journal\":{\"name\":\"2021 IFIP/IEEE International Symposium on Integrated Network Management (IM)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IFIP/IEEE International Symposium on Integrated Network Management (IM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21427/4VMV-G820\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IFIP/IEEE International Symposium on Integrated Network Management (IM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21427/4VMV-G820","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
To guarantee quality of delivery for video streaming over software defined networks, efficient predictors and adaptive routing frameworks are required. We demonstrate an agent that predicts video quality of delivery metrics in a scalable way using a bespoke codec-aware learning model. We also demonstrate the integration of this agent with an adaptive framework for centrally controlled software-defined networks that re-configures network operational paths in response to the learning agent, ensuring that good quality of delivery of video is maintained during periods of congestion. The demo scenario highlights the feasibility, scalability and accuracy of the framework.