Exploiting Network Awareness to Enhance DASH Over Wireless

TL;DR

This paper proposes a network-aware approach to optimize video delivery over wireless networks by exploiting infrastructure knowledge and request predictability, significantly improving user experience over traditional DASH methods.

Contribution

It introduces a novel method that leverages network awareness and request prediction to enhance DASH performance in wireless environments.

Findings

Improved throughput by distributing traffic over time.

Enhanced Quality of Experience for end users.

Effective use of core and edge network resources.

Abstract

The introduction of Dynamic Adaptive Streaming over HTTP (DASH) helped reduce the consumption of resource in video delivery, but its client-based rate adaptation is unable to optimally use the available end-to-end network bandwidth. We consider the problem of optimizing the delivery of video content to mobile clients while meeting the constraints imposed by the available network resources. Observing the bandwidth available in the network's two main components, core network, transferring the video from the servers to edge nodes close to the client, and the edge network, which is in charge of transferring the content to the user, via wireless links, we aim to find an optimal solution by exploiting the predictability of future user requests of sequential video segments, as well as the knowledge of available infrastructural resources at the core and edge wireless networks in a given future time window. Instead of regarding the bottleneck of the end-to-end connection as our throughput, we distribute the traffic load over time and use intermediate nodes between the server and the client for buffering video content to achieve higher throughput, and ultimately significantly improve the Quality of Experience for the end user in comparison with current solutions.