Network-aware video level encoding for uplink adaptive HTTP streaming

We study the uplink delivery of live video using adaptive HTTP streaming (AHS). In AHS, the process of simultaneously creating video levels at different rates is computationally demanding and quickly exceeds the computational capacity of mobile devices. As a remedy, we propose a network-aware video level selection approach which reduces the number of levels that need to be encoded. To this end, we develop an algorithm which selects a reduced set of video levels from a static pre-defined set based on TCP uplink throughput information. More specifically, during session start-up and after inter-RAN handovers, TCP uplink throughput information from a remote database is used while otherwise, actual TCP uplink throughput measurements are performed. We test the proposed approach in an automotive scenario to upstream the video of a vehicle's front-facing camera to a remote video portal. Our results show that our proposed network-aware video level selection approach leads to a significant reduction of the number of video levels that need to be encoded. At the same time, a similar quality of experience is achieved in terms of mean subjective quality of the delivered video segments, interrupted playback duration due to stalling events, and number of quality switches when compared to an implementation which considers the static full set of video levels.