Next Generation Packet Video Networking with Applied AI
具有应用人工智能的下一代分组视频网络
基本信息
- 批准号:RGPIN-2020-06273
- 负责人:
- 金额:$ 3.35万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2021
- 资助国家:加拿大
- 起止时间:2021-01-01 至 2022-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
It is safe to say that packet video has already taken over the Internet, when considering that video traffic constituted 75% of all IP traffic in 2017, and will constitute 82% of all IP traffic by 2022. Sandvine reports that 6 of the top 7 biggest consumers of global IP traffic in 2018 were packet video systems: NetFlix (15% of all IP traffic), HTTP Media Streaming (13%), YouTube (11%), MPEG-TS (4.4%), HTTPS (not video, 4.1%), the video steaming protocol QUIC (3.9%), and Amazon Prime Video (3.7%). These video services are also known as Over-The-Top (OTT) video, because they directly offer video to consumers over the Internet, instead of the traditional distribution approaches of cable, broadcast or satellite. A portion of this traffic is from Internet gaming, such as cloud gaming and online gaming, taking about 7.8% of all Internet traffic in 2018. Despite their relatively fast market penetration, packet video systems still face fundamental challenges that prevent their continuous growth: Quality of Experience (QoE) which relates to the satisfaction of users with their video service experience, delay which is important for conversational application, and fairness among multiple users sharing the same bottleneck network link. To address these challenges, in this project we study, design, and develop Artificial Intelligence based methods to eliminate or significantly reduce unsatisfactory experience of users in packet video systems and networks. The vision behind this goal; i.e., Applied AI for packet video systems and networks, will in fact continue beyond the 5 years of this proposal, since AI applied to packet video systems is a relatively young research area with huge potential and impact. The said project goal decomposes into the following objectives: fairness among multiple OTT video users; efficient resource utilization within the cloud, which will also lead to lower delay for live video; system parameter estimation, such as bandwidth, delay, buffer levels, etc.; saliency-based video coding for higher Quality of Experience (QoE); and fault detection and root-cause analysis. Beyond the 5-year period, the vision will continue with applying AI to the following: traffic classification which helps us further improve QoE and resource utilization; self-organizing networks that intelligently make routing and operation decision; automatic recommender systems, once the root-cause has been detected, to aid the network operator to more quickly fix the problem, or in some cases for the system itself to autonomously repair itself; and congestion control, instead of widely-used exact TCP algorithms. The project will also contribute to the training of HQP, industrial collaboration, and support of outreach activities.
可以肯定地说,分组视频已经接管了互联网,考虑到2017年视频流量占所有IP流量的75%,到2022年将占所有IP流量的82%。Sandvine报告称,2018年全球IP流量的前7大消费者中有6个是分组视频系统:NetFlix(占所有IP流量的15%),HTTP媒体流(13%),YouTube(11%),MPEG-TS(4.4%),HTTPS(非视频,4.1%),视频流协议QUIC(3.9%)和Amazon Prime Video(3.7%)。这些视频服务也被称为过顶(OTT)视频,因为它们通过互联网直接向消费者提供视频,而不是传统的有线电视,广播或卫星分销方式。其中一部分流量来自互联网游戏,如云游戏和在线游戏,约占2018年所有互联网流量的7.8%。尽管其相对快速的市场渗透,分组视频系统仍然面临着基本的挑战,阻止其持续增长:体验质量(QoE),涉及用户的满意度与他们的视频服务体验,延迟是重要的会话应用程序,和公平性之间的多个用户共享相同的瓶颈网络链路。为了应对这些挑战,在这个项目中,我们研究,设计和开发基于人工智能的方法,以消除或显着减少分组视频系统和网络中用户的不满意体验。这一目标背后的愿景;即,事实上,用于分组视频系统和网络的应用AI将持续超过该提案的5年,因为应用于分组视频系统的AI是一个相对年轻的研究领域,具有巨大的潜力和影响。上述项目目标分解为以下目标:多个OTT视频用户之间的公平性;云内资源的有效利用,这也将导致直播视频的延迟降低;系统参数估计,如带宽,延迟,缓冲水平等;基于显著性的视频编码,以实现更高的体验质量(QoE);以及故障检测和根本原因分析。未来5年,我们将继续将人工智能应用于以下领域:流量分类,帮助我们进一步提高QoE和资源利用率;自组织网络,智能地做出路由和运营决策;一旦已经检测到根本原因,自动推荐系统就帮助网络运营商更快地解决问题,或者在某些情况下用于系统自身自主地修复自身;以及拥塞控制,而不是广泛使用的精确TCP算法。该项目还将有助于培训人力资源规划人员、工业合作和支持外联活动。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Shirmohammadi, Shervin其他文献
An Empirical Approach to Modeling User-System Interaction Conflicts in Smart Homes
- DOI:
10.1109/thms.2020.3017784 - 发表时间:
2020-12-01 - 期刊:
- 影响因子:3.6
- 作者:
Miandashti, Fereshteh Jadidi;Izadi, Mohammad;Shirmohammadi, Shervin - 通讯作者:
Shirmohammadi, Shervin
A New Hand-Measurement Method to Simplify Calibration in CyberGlove-Based Virtual Rehabilitation
- DOI:
10.1109/tim.2010.2057712 - 发表时间:
2010-10-01 - 期刊:
- 影响因子:5.6
- 作者:
Zhou, Jilin;Malric, Francois;Shirmohammadi, Shervin - 通讯作者:
Shirmohammadi, Shervin
Multiple Description Coding for Best-Effort Delivery of Light Field Video Using GNN-Based Compression
- DOI:
10.1109/tmm.2021.3129918 - 发表时间:
2023-01-01 - 期刊:
- 影响因子:7.3
- 作者:
Hu, Xinjue;Pan, Yuxuan;Shirmohammadi, Shervin - 通讯作者:
Shirmohammadi, Shervin
Video Encoding Acceleration in Cloud Gaming
- DOI:
10.1109/tcsvt.2015.2452778 - 发表时间:
2015-12-01 - 期刊:
- 影响因子:8.4
- 作者:
Semsarzadeh, Mehdi;Yassine, Abdulsalam;Shirmohammadi, Shervin - 通讯作者:
Shirmohammadi, Shervin
Machine Learning in Measurement Part 1: Error Contribution and Terminology Confusion
- DOI:
10.1109/mim.2021.9400955 - 发表时间:
2021-04-01 - 期刊:
- 影响因子:2.1
- 作者:
Shirmohammadi, Shervin;Al Osman, Hussein - 通讯作者:
Al Osman, Hussein
Shirmohammadi, Shervin的其他文献
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{{ truncateString('Shirmohammadi, Shervin', 18)}}的其他基金
Next Generation Packet Video Networking with Applied AI
具有应用人工智能的下一代分组视频网络
- 批准号:
RGPIN-2020-06273 - 财政年份:2022
- 资助金额:
$ 3.35万 - 项目类别:
Discovery Grants Program - Individual
Next Generation Packet Video Networking with Applied AI
具有应用人工智能的下一代分组视频网络
- 批准号:
RGPIN-2020-06273 - 财政年份:2020
- 资助金额:
$ 3.35万 - 项目类别:
Discovery Grants Program - Individual
Delay-Sensitive Server Selection System for Online Multiuser Collaboration
用于在线多用户协作的延迟敏感服务器选择系统
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561214-2020 - 财政年份:2020
- 资助金额:
$ 3.35万 - 项目类别:
Alliance Grants
HiPer clouding: high performance cloud gaming
HiPer云:高性能云游戏
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506890-2017 - 财政年份:2019
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$ 3.35万 - 项目类别:
Strategic Projects - Group
Multi-Camera Panorama Generation with Uncalibrated Camera
未校准相机的多相机全景生成
- 批准号:
533239-2018 - 财政年份:2018
- 资助金额:
$ 3.35万 - 项目类别:
Engage Grants Program
HiPer clouding: high performance cloud gaming
HiPer云:高性能云游戏
- 批准号:
506890-2017 - 财政年份:2018
- 资助金额:
$ 3.35万 - 项目类别:
Strategic Projects - Group
Mobile Cloud Gaming Systems and Virtual Environments
移动云游戏系统和虚拟环境
- 批准号:
RGPIN-2014-06451 - 财政年份:2018
- 资助金额:
$ 3.35万 - 项目类别:
Discovery Grants Program - Individual
Mobile Cloud Gaming Systems and Virtual Environments
移动云游戏系统和虚拟环境
- 批准号:
RGPIN-2014-06451 - 财政年份:2017
- 资助金额:
$ 3.35万 - 项目类别:
Discovery Grants Program - Individual
HiPer clouding: high performance cloud gaming
HiPer云:高性能云游戏
- 批准号:
506890-2017 - 财政年份:2017
- 资助金额:
$ 3.35万 - 项目类别:
Strategic Projects - Group
Mobile Cloud Gaming Systems and Virtual Environments
移动云游戏系统和虚拟环境
- 批准号:
RGPIN-2014-06451 - 财政年份:2016
- 资助金额:
$ 3.35万 - 项目类别:
Discovery Grants Program - Individual
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