SDN Based QoE Optimization for HTTP-Based Adaptive Video Streaming

Abstract

Rapidly increasing volume of video streaming traffic creates a bandwidth crunch for service providers and network operators. Increased user expectations for higher quality video does not imply their willingness to pay higher monthly fees. Hence, more efficient bandwidth management schemes are needed to bridge the gap between growing demand from video traffic and existing network infrastructure. In this work, we present a novel bandwidth management solution for optimizing overall quality of experience (QoE) of multiple video streaming sessions. Instead of allocating bandwidth equally among competing flows, we propose to tailor the bandwidth allocation to both content complexity of requested video and playout buffer status of individual clients. We formulate the multi client bandwidth allocation problem within the convex optimization framework, which is flexible enough to accommodate a wide variety of video quality metrics. Further, we present a practical architecture based on software defined networking (SDN) with two components: video quality monitoring and video quality optimization. Testbed-based experiments confirm that with quality-optimized allocation the network can support up to 75% more users at the same level of quality-of-experience (QoE) than conventional equal-rate allocations.