On managing quality of experience of multiple video streams in wireless networks

Abstract

Managing the Quality-of-Experience (QoE) of video streaming for wireless clients is becoming increasingly important due to the rapid growth of video traffic on wireless networks. The inherent variability of the wireless channel as well as the Variable Bit Rate (VBR) of the compressed video streams make QoE management a challenging problem. Prior work has studied this problem in the context of transmitting a single video stream. In this paper, we investigate multiplexing schemes to transmit multiple video streams from a base station to mobile clients that use number of playout stalls as a performance metric.In this context, we present an epoch-by-epoch framework to fairly allocate wireless transmission slots to streaming videos. In each epoch our scheme essentially reduces the vulnerability to stalling by allocating slots to videos in a way that maximizes the minimum 'playout lead' across all videos. Next, we show that the problem of allocating slots fairly is NP-complete even for a constant number of videos. We then present a fast lead-aware greedy algorithm for the problem. Our choice of greedy algorithm is motivated by the fact that this algorithm is optimal when the channel quality of a user remains unchanged within an epoch (but different users may experience different channel quality). Moreover, our experimental results based on public MPEG-4 video traces and wireless channel traces that we collected from a WiMAX test-bed show that the lead-aware greedy approach performs a fair distribution of stalls across the clients when compared to other algorithms, while still maintaining similar or lower average number of stalls per client.

QoE in video streaming over wireless networks: perspectives and research challenges

“…A study of managing playout stalls for transmitting multiple video streams from a base station to mobile clients was conducted in [39]. A fast playout lead-aware greedy algorithm is designed for multiplexing videos.…”

Smart routing: Fine-grained stall management of video streams in mobile core networks

“…In particular, stalling is very detrimental to the QoE of video streams [17]. Hence, in this paper, we specifically focus on stall management and aim to provide fine-grained traffic control for video streams in an evolving mobile core network as depicted in Fig.…”

“…Depending on the data transmission and the stall-recovery scheme, a stall lasts for certain duration, referred to as stall delay. The term playout lead is adopted from [17], and represents the duration of time that the video can be played using only the data already buffered in the mobile device.…”

“…We consider video streams that are delivered in a progressive downloading mode, i.e., a mobile device could buffer up to the entire video clip in its local memory. We also assume that the data consuming information at the buffer of remote devices can be efficiently tracked or estimated by core networks and is readily accessible to the controller [17] in the system under study. For example, in an LTE system, the amount of data delivered to remote devices is gathered by the policy and charging rules function (PCRF) component.…”

“…The playback characteristic of a video is an essential factor that can be exploited to manage stalls and improve QoE. In [17], Dutta et al defined the playout lead and attempted to prevent stalls by maximizing the minimum lead over multiple streams. Likewise, Liang and Liang aimed to reduce stall delay by adapting variable bit-rate of video streams to dynamic wireless channels and user buffer [19].…”