Prius: Hybrid Edge Cloud and Client Adaptation for HTTP Adaptive Streaming in Cellular Networks

Abstract

In this paper, we present Prius, a hybrid edge cloud and client adaptation framework for HTTP adaptive streaming (HAS) by taking advantage of the new capabilities empowered by recent advances in edge cloud computing. In particular, emerging edge clouds are capable of accessing application-layer and radio access networks (RAN) information in real time. Coupled with powerful computation support, an edge cloud assisted strategy is expected to significantly enrich mobile services. Meanwhile, although HAS has established itself as the dominant technology for video streaming, one key challenge for adapting HAS to mobile cellular networks is in overcoming the inaccurate bandwidth estimation and unfair bitrate adaptation under the highly dynamic cellular links. Edge cloud assisted HAS presents a new opportunity to resolve these issues and achieve systematic enhancement of quality of experience (QoE) and QoE fairness in cellular networks.To explore this new opportunity, Prius overlays a layer of adaptation intelligence at the edge cloud to finalize the adaptation decisions while considering the initial bandwidth-irrelevant bitrate selection at the clients. Prius is able to exploit RAN channel status, client device characteristics as well as applicationlayer information in order to jointly adapt the bitrate of multiple clients. Prius also adopts a QoE continuum model to track the cumulative viewing experience and an exponential smoothing estimation to accurately estimate future channel under different moving patterns. Extensive trace-driven simulation results show that Prius with hybrid edge cloud and client adaptation is promising under both slow and fast moving environment. Furthermore, Prius adaptation algorithm achieves a near-optimal performance that outperforms exiting strategies.

A Survey on Bitrate Adaptation Schemes for Streaming Media Over HTTP

“…To reduce video instability, QoE unfairness and stalls in cellular networks, Yan et al [126] designed Prius as a framework that consists of a hybrid edge cloud and a client-based adaptation scheme. Similarly, Zahran et al [127] proposed a Stall-aware Pacing (SAP) traffic management solution for DASH clients.…”

Video Caching, Analytics, and Delivery at the Wireless Edge: A Survey and Future Directions

“…A QoE model at the network edge can use the resolution of delivered video segments as a measure of QoE [95]. Additional indicators of QoE are represented by the cumulative state of playback in terms of video stalls [96] or effective loss rate over the communication channel [97]. Khan et al [98] propose a QoE model for video streaming which leverages a non-linear function of content type and sender bitrate to predict QoE.…”

Edge Computing Assisted Adaptive Streaming Scheme for Mobile Networks

“…Yan et al have proposed a hybrid edge cloud and client adaptation scheme for the HAS in cellular networks [26]. The edge cloud performs the joint optimization of QoE and fairness by using the information of RAN and application.…”

“…We compare the performance of the proposed scheme with the existing edge computing-assisted adaptive streaming schemes. In the performance evaluation, we refer to these schemes proposed in [25] and [26] as ECAA and Prius, respectively. The ECAA is an edge computingassisted adaptive mobile video streaming scheme that includes the clients to the edge servers mapping and the joint optimization of QoE and fairness.…”