{"title":"有期限和优先级限制的沉浸式视频流传输调度","authors":"Tongtong Feng, Qi Qi, Bo He, Jingyu Wang","doi":"arxiv-2408.17028","DOIUrl":null,"url":null,"abstract":"Deadline-aware transmission scheduling in immersive video streaming is\ncrucial. The objective is to guarantee that at least a certain block in\nmulti-links is fully delivered within their deadlines, which is referred to as\ndelivery ratio. Compared with existing models that focus on maximizing\nthroughput and ultra-low latency, which makes bandwidth resource allocation and\nuser satisfaction locally optimized, immersive video streaming needs to\nguarantee more high-priority block delivery within personalized deadlines. In\nthis paper, we propose a deadline and priority-constrained immersive video\nstreaming transmission scheduling scheme. It builds an accurate bandwidth\nprediction model that can sensitively assist scheduling decisions. It divides\nvideo streaming into various media elements and performs scheduling based on\nthe user's personalized latency sensitivity thresholds and the media element's\npriority. We evaluate our scheme via trace-driven simulations. Compared with\nexisting models, the results further demonstrate the superiority of our scheme\nwith 12{\\%}-31{\\%} gains in quality of experience (QoE).","PeriodicalId":501280,"journal":{"name":"arXiv - CS - Networking and Internet Architecture","volume":"26 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Deadline and Priority Constrained Immersive Video Streaming Transmission Scheduling\",\"authors\":\"Tongtong Feng, Qi Qi, Bo He, Jingyu Wang\",\"doi\":\"arxiv-2408.17028\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Deadline-aware transmission scheduling in immersive video streaming is\\ncrucial. The objective is to guarantee that at least a certain block in\\nmulti-links is fully delivered within their deadlines, which is referred to as\\ndelivery ratio. Compared with existing models that focus on maximizing\\nthroughput and ultra-low latency, which makes bandwidth resource allocation and\\nuser satisfaction locally optimized, immersive video streaming needs to\\nguarantee more high-priority block delivery within personalized deadlines. In\\nthis paper, we propose a deadline and priority-constrained immersive video\\nstreaming transmission scheduling scheme. It builds an accurate bandwidth\\nprediction model that can sensitively assist scheduling decisions. It divides\\nvideo streaming into various media elements and performs scheduling based on\\nthe user's personalized latency sensitivity thresholds and the media element's\\npriority. We evaluate our scheme via trace-driven simulations. Compared with\\nexisting models, the results further demonstrate the superiority of our scheme\\nwith 12{\\\\%}-31{\\\\%} gains in quality of experience (QoE).\",\"PeriodicalId\":501280,\"journal\":{\"name\":\"arXiv - CS - Networking and Internet Architecture\",\"volume\":\"26 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Networking and Internet Architecture\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2408.17028\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Networking and Internet Architecture","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.17028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Deadline and Priority Constrained Immersive Video Streaming Transmission Scheduling
Deadline-aware transmission scheduling in immersive video streaming is
crucial. The objective is to guarantee that at least a certain block in
multi-links is fully delivered within their deadlines, which is referred to as
delivery ratio. Compared with existing models that focus on maximizing
throughput and ultra-low latency, which makes bandwidth resource allocation and
user satisfaction locally optimized, immersive video streaming needs to
guarantee more high-priority block delivery within personalized deadlines. In
this paper, we propose a deadline and priority-constrained immersive video
streaming transmission scheduling scheme. It builds an accurate bandwidth
prediction model that can sensitively assist scheduling decisions. It divides
video streaming into various media elements and performs scheduling based on
the user's personalized latency sensitivity thresholds and the media element's
priority. We evaluate our scheme via trace-driven simulations. Compared with
existing models, the results further demonstrate the superiority of our scheme
with 12{\%}-31{\%} gains in quality of experience (QoE).