A Hybrid NDN-IP Architecture for Live Video Streaming: From Host-Based to Content-Based Delivery to Improve QoE

Author:

Dasgupta Ishita1,Shannigrahi Susmit2,Zink Michael3

Affiliation:

1. College of Information and Computer Sciences, University of Massachusetts Amherst, 140 Governors Drive, Amherst, MA 01002, USA

2. Computer Science Department, Tennessee Tech University, 331 Bruner Hall, Cookeville, Tennessee 38501, USA

3. Electrical and Computer Engineering, University of Massachusetts Amherst, 213B Knowles Engineering Building, Amherst, MA, 01002, USA

Abstract

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.

Funder

National Science Foundation

Publisher

World Scientific Pub Co Pte Ltd

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Linguistics and Language,Information Systems,Software

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Science DMZ Networks: How Different Are They Really?;2024 IEEE 49th Conference on Local Computer Networks (LCN);2024-10-08

2. PCLive: Bringing Named Data Networking to Internet Livestreaming;Proceedings of the 10th ACM Conference on Information-Centric Networking;2023-10-08

3. Capture and Analysis of Traffic Traces on a Wide-Area NDN Testbed;Proceedings of the 10th ACM Conference on Information-Centric Networking;2023-10-08

4. The Emerging of Named Data Networking: Architecture, Application, and Technology;IEEE Access;2023

5. Forwarding and caching in video streaming over ICSDN: A clean-slate publish-subscribe approach;Computer Networks;2022-12

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3