piStream

Abstract

Adaptive HTTP video streaming over LTE has been gaining popularity due to LTE's high capacity. Quality of adaptive streaming depends highly on the accuracy of client's estimation of end-to-end network bandwidth, which is challenging due to LTE link dynamics. In this paper, we present piStream, that allows a client to efficiently monitor the LTE basestation's PHY-layer resource allocation, and then map such information to an estimation of available bandwidth. Given the PHY-informed bandwidth estimation, piStream uses a probabilistic algorithm to balance video quality and the risk of stalling, taking into account the burstiness of LTE downlink traffic loads. We conduct a real-time implementation of piStream on a software-radio tethered to an LTE smartphone. Comparison with state-of-the-art adaptive streaming protocols demonstrates that piStream can effectively utilize the LTE bandwidth, achieving high video quality with minimal stalling rate.

Octopus: Exploiting the Edge Intelligence for Accessible 5G Mobile Performance Enhancement

“…As a persistent problem along with the Internet's evolution, (i) TCP evolves from traditionally newReno [78], Cubic [48] to BBR [30] and PCC [79], and has also tailed for cellular networks [20], [80], [81], [82], or for better delivering real-time video [83], [84], [85]. (ii) Video streaming ABR algorithms are traditionally designed based on instantaneous throughput and buffer-level [67], [86], or further enhanced by physical layer information [22]. Emerging algorithms adopt machine learning for QoE optimization [87], [88], [89].…”

“…As an edge service, Octopus is lightweight, which only involves software-level changes on MEC and backend application servers, and evades hardware/firmware changes and root/system privilege on the UE/gNB, unlike existing solutions [20], [21], [22]. Meanwhile, Octopus is a pioneering and feasible solution for future cellular NEF (Network Exposure Function) on seamless 5G mobility management.…”

Cross-layer host-network co-design for QoS in streamed video data networking

“…Different from prior studies that estimate network throughput based on feedback from the transport layer, piStream [180] harnesses physical layer information to enhance video streaming quality over Long-Term Evolution (LTE) networks. Obtaining resource allocation details from the physical layer, particularly by decoding the downlink control channel, is computationally demanding and requires hardware alterations.…”