In China, currently there are more than 100 million videos being watched everyday on the Internet. There are three kinds of Internet videos: video sharing, Video on Demand (VoD), and Peer-to-Peer (P2P) streaming media...In China, currently there are more than 100 million videos being watched everyday on the Internet. There are three kinds of Internet videos: video sharing, Video on Demand (VoD), and Peer-to-Peer (P2P) streaming media. Video sharing is based on browser/server mode, severing user generated content. VoD is based on client/server mode and needs to be paid for. P2P streaming media is based on P2P mode service for hot content. To address P2P traffic optimization and content regulation, China National Information Technology Standardization Technical Committee sets up P2P working group to make relevant standards.展开更多
Benefiting from the improvements of Internet infrastructure and video coding technology, online video services are becoming a new favorite form of video entertainment.However, most of the existing video quality assess...Benefiting from the improvements of Internet infrastructure and video coding technology, online video services are becoming a new favorite form of video entertainment.However, most of the existing video quality assessment methods are designed for broadcasting/cable televisions and it is still an open issue how to assess and measure the quality of online video services. In this paper, we survey the state-of-the-art video streaming technologies, and present a framework of quality assessment and measurement for Internet video streaming. This paper introduces several metrics for user's quality of experience(QoE).These QoE metrics are classified into two categories: objective metrics and subjective metrics. It is different for service participators to measure objective and subjective metrics.The QoE measurement methodologies consist of client-side, server-side, and in-network measurement.展开更多
With the rapid development of Internet around the world, network is transmitting all kinds of information to human beings nowadays. Net news, also called cyber news is affecting people’s expression of daily English. ...With the rapid development of Internet around the world, network is transmitting all kinds of information to human beings nowadays. Net news, also called cyber news is affecting people’s expression of daily English. A large number of cyber words, phrases even sentences, which are different from conventional English, are formed and become popular in the cyber world. This paper discusses different markers of net news by taking Internet video news and Internet audio news as examples so that the readers can fully understand the properties of net news.展开更多
Real-time video transport over wireless Internet faces many challenges due to the heterogeneous environment including wireline and wireless networks. A robust network condition classification algorithm using multiple ...Real-time video transport over wireless Internet faces many challenges due to the heterogeneous environment including wireline and wireless networks. A robust network condition classification algorithm using multiple end-to-end metrics and Support Vector Machine (SVM) is proposed to classify different network events and model the transition pattern of network conditions. End-to-end Quality-of-Service (QoS) mechanisms like congestion control, error control, and power control can benefit from the network condition information and react to different network situations appropriately. The proposed network condition classifica- tion algorithm uses SVM as a classifier to cluster different end-to-end metrics such as end-to-end delay, delay jitter, throughput and packet loss-rate for the UDP traffic with TCP-friendly Rate Control (TFRC), which is used for video transport. The algorithm is also flexible for classifying different numbers of states representing different levels of network events such as wireline congestion and wireless channel loss. Simulation results using network simulator 2 (ns2) showed the effectiveness of the proposed scheme.展开更多
云网资源与视频任务的高效调度是保障视频物联网(video Internet of things,VIoT)应用性能的关键.然而,目前运营化VIoT所用调度算法对差异化的任务需求和高度动态的云网资源变化适应能力不足,导致VIoT应用性能不佳.针对上述问题,提出了...云网资源与视频任务的高效调度是保障视频物联网(video Internet of things,VIoT)应用性能的关键.然而,目前运营化VIoT所用调度算法对差异化的任务需求和高度动态的云网资源变化适应能力不足,导致VIoT应用性能不佳.针对上述问题,提出了一种基于连续学习的视频物联网任务需求理解与调度方法(continuous learning-based task demand understanding and scheduling method for VIoT,CLTUS).与传统启发式或机器学习驱动的调度算法不同,将连续学习引入云网资源与视频任务需求的匹配中.首先,基于通用的连续学习框架实现各类视频任务需求的准确理解;其次,依据视频任务之间的需求依赖关系,实现任务与服务器的适配,以精细化调度云网资源;最后,将所提方法部署于软件定义的VIoT实验平台上.与传统方法相比,CLTUS不仅将视频任务的平均处理效率提高了127.73%,还将云网资源利用均衡率提高至67.2%,有效增强了VIoT应用性能.展开更多
文摘In China, currently there are more than 100 million videos being watched everyday on the Internet. There are three kinds of Internet videos: video sharing, Video on Demand (VoD), and Peer-to-Peer (P2P) streaming media. Video sharing is based on browser/server mode, severing user generated content. VoD is based on client/server mode and needs to be paid for. P2P streaming media is based on P2P mode service for hot content. To address P2P traffic optimization and content regulation, China National Information Technology Standardization Technical Committee sets up P2P working group to make relevant standards.
基金supported by National Key R&D Program of China No.2018YFB0803702Beijing Culture Development Funding under Grant No.2016-288Toutiao Funding No.ZN20171224003
文摘Benefiting from the improvements of Internet infrastructure and video coding technology, online video services are becoming a new favorite form of video entertainment.However, most of the existing video quality assessment methods are designed for broadcasting/cable televisions and it is still an open issue how to assess and measure the quality of online video services. In this paper, we survey the state-of-the-art video streaming technologies, and present a framework of quality assessment and measurement for Internet video streaming. This paper introduces several metrics for user's quality of experience(QoE).These QoE metrics are classified into two categories: objective metrics and subjective metrics. It is different for service participators to measure objective and subjective metrics.The QoE measurement methodologies consist of client-side, server-side, and in-network measurement.
文摘With the rapid development of Internet around the world, network is transmitting all kinds of information to human beings nowadays. Net news, also called cyber news is affecting people’s expression of daily English. A large number of cyber words, phrases even sentences, which are different from conventional English, are formed and become popular in the cyber world. This paper discusses different markers of net news by taking Internet video news and Internet audio news as examples so that the readers can fully understand the properties of net news.
基金Project supported by the Croucher Foundation Fellowship fromHong Kong, China
文摘Real-time video transport over wireless Internet faces many challenges due to the heterogeneous environment including wireline and wireless networks. A robust network condition classification algorithm using multiple end-to-end metrics and Support Vector Machine (SVM) is proposed to classify different network events and model the transition pattern of network conditions. End-to-end Quality-of-Service (QoS) mechanisms like congestion control, error control, and power control can benefit from the network condition information and react to different network situations appropriately. The proposed network condition classifica- tion algorithm uses SVM as a classifier to cluster different end-to-end metrics such as end-to-end delay, delay jitter, throughput and packet loss-rate for the UDP traffic with TCP-friendly Rate Control (TFRC), which is used for video transport. The algorithm is also flexible for classifying different numbers of states representing different levels of network events such as wireline congestion and wireless channel loss. Simulation results using network simulator 2 (ns2) showed the effectiveness of the proposed scheme.
文摘云网资源与视频任务的高效调度是保障视频物联网(video Internet of things,VIoT)应用性能的关键.然而,目前运营化VIoT所用调度算法对差异化的任务需求和高度动态的云网资源变化适应能力不足,导致VIoT应用性能不佳.针对上述问题,提出了一种基于连续学习的视频物联网任务需求理解与调度方法(continuous learning-based task demand understanding and scheduling method for VIoT,CLTUS).与传统启发式或机器学习驱动的调度算法不同,将连续学习引入云网资源与视频任务需求的匹配中.首先,基于通用的连续学习框架实现各类视频任务需求的准确理解;其次,依据视频任务之间的需求依赖关系,实现任务与服务器的适配,以精细化调度云网资源;最后,将所提方法部署于软件定义的VIoT实验平台上.与传统方法相比,CLTUS不仅将视频任务的平均处理效率提高了127.73%,还将云网资源利用均衡率提高至67.2%,有效增强了VIoT应用性能.
