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Title: A Hybrid NDN-IP Architecture for Live Video Streaming: From Host-Based to Content-Based Delivery to Improve QoE
With live video streaming becoming accessible in various applications on all client platforms, it is imperative to create a seamless and efficient distribution system that is flexible enough to choose from multiple Internet architectures best suited for video streaming (live, on-demand, AR). In this paper, we highlight the benefits of such a hybrid system for live video streaming as well as present a detailed analysis with the goal to provide a high quality of experience (QoE) for the viewer. For our hybrid architecture, video streaming is supported simultaneously over TCP/IP and Named Data Networking (NDN)-based architecture via operating system and networking virtualization techniques to design a flexible system that utilizes the benefits of these varying Internet architectures. Also, to relieve users from the burden of installing a new protocol stack (in the case of NDN) on their devices, we developed a lightweight solution in the form of a container that includes the network stack as well as the streaming application. At the client, the required Internet architecture (TCP/IP versus NDN) can be selected in a transparent and adaptive manner. Based on a prototype, we have designed and implemented maintaining efficient use of network resources, we demonstrate that in the case of live streaming, NDN achieves better QoE per client than IP and can also utilize higher than allocated bandwidth through in-network caching. Even without caching, as opposed to IP-only, our hybrid setup achieves better average bitrate and better perceived visual quality (computed via VMAF metric) over live video streaming services. Furthermore, we present detailed analysis on ways adaptive video streaming with NDN can be further improved with respect to QoE.  more » « less
Award ID(s):
1901137
NSF-PAR ID:
10341386
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
International Journal of Semantic Computing
Volume:
16
Issue:
02
ISSN:
1793-351X
Page Range / eLocation ID:
163 to 187
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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