Optimal Network-Assisted Multi-user DASH Video Streaming
This addresses video streaming bottlenecks at network edges for users, but it is incremental as it builds on existing DASH protocols.
The paper tackled the problem of minimizing video stalling in multi-user DASH streaming at edge servers by proposing a resource allocation mechanism that schedules users based on deadlines, proving its optimality for fixed loss rates and verifying utility in realistic simulations.
Streaming video is becoming the predominant type of traffic over the Internet with reports forecasting the video content to account for 80% of all traffic by 2019. With significant investment on Internet backbone, the main bottleneck remains at the edge servers (e.g., WiFi access points, small cells, etc.). In this work, we propose and prove the optimality of a multiuser resource allocation mechanism operating at the edge server that minimizes the probability of stalling of video streams due to buffer under-flows. Our proposed policy utilizes Media Presentation Description (MPD) files of clients that are sent in compliant to Dynamic Adaptive Streaming over HTTP (DASH) protocol to be cognizant of the deadlines of each of the media file to be displayed by the clients. Then, the policy schedules the users in the order of their deadlines. After establishing the optimality of this policy to minimize the stalling probability for a network with links associated with fixed loss rates, the utility of the algorithm is verified under realistic network conditions with detailed NS-3 simulations.