{"title":"Viewport Prediction via Adaptive Edge Offloading","authors":"Ahmet Gunhan Aydin;Haris Vikalo","doi":"10.1109/LNET.2024.3480149","DOIUrl":null,"url":null,"abstract":"The pursuit of enhanced interactive visual experiences has created growing interest in 360-degree video streaming. However, transmitting such content requires significant bandwidth compared to conventional planar video, motivating a search for effective bandwidth optimization strategies. A promising approach involves predicting viewport and prioritizing transmission of the regions of interest at higher quality. The existing methods for viewport prediction rely on sophisticated neural networks hosted on servers and face major bandwidth and latency challenges. This letter proposes a hierarchical approach to viewport prediction that leverages a small model on edge devices and offloads to the server only the most challenging tasks. The offloading algorithm relies on rate control to maximize the performance while meeting resource constraints, presenting a novel solution to bandwidth-efficient viewport prediction for 360-degree video streaming.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"7 1","pages":"21-25"},"PeriodicalIF":0.0000,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Networking Letters","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10716548/","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
The pursuit of enhanced interactive visual experiences has created growing interest in 360-degree video streaming. However, transmitting such content requires significant bandwidth compared to conventional planar video, motivating a search for effective bandwidth optimization strategies. A promising approach involves predicting viewport and prioritizing transmission of the regions of interest at higher quality. The existing methods for viewport prediction rely on sophisticated neural networks hosted on servers and face major bandwidth and latency challenges. This letter proposes a hierarchical approach to viewport prediction that leverages a small model on edge devices and offloads to the server only the most challenging tasks. The offloading algorithm relies on rate control to maximize the performance while meeting resource constraints, presenting a novel solution to bandwidth-efficient viewport prediction for 360-degree video streaming.