Balancing Quality of Experience and Traffic Volume in Adaptive Bitrate Streaming

Adaptive bitrate (ABR) streaming services have spread with advances in the codec, video streaming, and network technologies. For smooth playback ABR services, a player runs an algorithm, which dynamically adjusts of data on basis statuses player. Existing algorithms calculate suitable to maximize quality experience (QoE). However, providing high-QoE increases investment costs content delivery (CDN) usage fees. According survey conducted by Streaming Video Alliance, mobile users prefer low-traffic videos videos. To reduce traffic volume, commercial video-streaming enable set upper limit bitrate. this cannot always achieve required QoE because they select high even when communication environment improves during viewing. In paper, we propose BANQUET, novel algorithm that can volume while maintaining above target QoE. The be or providers considering user's preferences CDN budget. BANQUET selects estimating will experienced all patterns for next several chunks future throughput buffer transition calculation. trace-based simulation showed reduces 18.3%-51.2% average 1.2%-38.3% broadband same as better than existing algorithms.