Generating Dynamic Adaptive Streaming over HTTP Traffic Flows with TEACUP Testbed
نویسندگان
چکیده
HTTP-based video streaming has become popular in recent years, with Dynamic Adaptive Streaming over HTTP (DASH) emerging as an ISO/IEC standard for live and on-demand video streaming services. Netflix and YouTube employ DASH-like streaming strategies and account for more than 50% of North American traffic in 2015, representing a significant source of Internet traffic. Consumer video streams are most likely to be bottlenecked by last-mile ISP links and impacted by emerging Active Queue Management (AQM) schemes for counteracting bufferbloat. However, the interactions between different TCP algorithms, DASH traffic (within a mix of other typical traffic) and the underlying AQMs are not well understood. Experiments in a controlled testbed allow shedding more light on this issue. We extended “TCP Experiment Automation Controlled Using Python” (TEACUP) to use dash.js and VLC clients for running repeatable DASH experiment trials with different TCP algorithms over a range of emulated network conditions, bottleneck rate limits and AQMs.
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