User-level fairness delivered: Network resource allocation for adaptive video streaming

HTTP adaptive streaming (HAS) technology is becoming a popular vehicle for online video delivery. HAS applications often compete for network resources without any coordination between each other in a shared network. This leads to quality of experience (QoE) fluctuations and unfairness between end users. This paper introduces a user-level fairness model (UF) which exploits video quality, switching impact and cost efficiency as the fairness metrics to achieve user-level fairness in resource allocation. Experimental results demonstrate how this model is a foundation to orchestrate the resource consumption of HAS streams.