A Lightpath Provisioning Method for Video Content Caching and Streaming Services in Elastic Optical Networks

Author(s):  
Akihiro Fujimoto ◽  
Yusuke Hirota ◽  
Hideki Tode
Author(s):  
Zhengkai Shi ◽  
Yipeng Zhou ◽  
Di Wu ◽  
Chen Wang

2018 ◽  
Vol 36 (15) ◽  
pp. 3142-3149 ◽  
Author(s):  
Francesco Paolucci ◽  
Andrea Sgambelluri ◽  
Filippo Cugini ◽  
Piero Castoldi

2014 ◽  
Vol 60 (3) ◽  
pp. 436-444 ◽  
Author(s):  
Demóstenes Z. Rodríguez ◽  
Renata L. Rosa ◽  
Eduardo A. Costa ◽  
Julia Abrahão ◽  
Graca Bressan

This paper proposes an architecture of content delivery network (CDN) based on big data for power saving. There are two types of video content: hot content and cold content. When video content is accessed frequently, it is called hot content. Conversely, when video content is accessed infrequently, it is called cold content. In CDN, there is an origin server and a CDN cache server. A CDN cache server has a replicated content and provides its content to the end users nearby. Therefore, the user can receive the requested content from the closest proximity for fast content. The proposed architecture in this paper powers off the cold content server in CDN cache server when the number of cold content requests decreases. Hence, the proposed architecture for content delivery services based on power saving is expected to be useful for providing multimedia streaming services with low power consumption for content providers.


2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Hyeonho Song ◽  
Kunwoo Park ◽  
Meeyoung Cha

AbstractLive streaming services enable the audience to interact with one another and the streamer over live content. The surging popularity of live streaming platforms has created a competitive environment. To retain existing viewers and attract newcomers, streamers and fans often create a well-condensed summary of the streamed content. However, this process is manual and costly due to the length of online live streaming events. The current study identifies enjoyable moments in user-generated live video content by examining the audiences’ collective evaluation of its epicness. We characterize what features “epic” moments and present a deep learning model to extract them based on analyzing two million user-recommended clips and the associated chat conversations. The evaluation shows that our data-driven approach can identify epic moments from user-generated streamed content that cover various contexts (e.g., victory, funny, awkward, embarrassing). Our user study further demonstrates that the proposed automatic model performs comparably to expert suggestions. We discuss implications of the collective decision-driven extraction in identifying diverse epic moments in a scalable way.


2021 ◽  
Vol 11 (23) ◽  
pp. 11267
Author(s):  
Achraf Gazdar ◽  
Lotfi Hidri ◽  
Belgacem Ben Ben Youssef ◽  
Meriam Kefi

Video streaming services are one of the most resource-consuming applications on the Internet. Thus, minimizing the consumed resources at runtime in general and the server/network bandwidth in particular are still challenging for researchers. Currently, most streaming techniques used on the Internet open one stream per client request, which makes the consumed bandwidth increases linearly. Hence, many broadcasting/streaming protocols have been proposed in the literature to minimize the streaming bandwidth. These protocols can be divided into two main categories, namely, reactive and proactive broadcasting protocols. While the first category is recommended for streaming unpopular videos, the second category is recommended for streaming popular videos. In this context, in this paper we propose an enhanced version of the reactive protocol Slotted Stream Tapping (SST) called Share All SST (SASST), which we prove to further reduce the streaming bandwidth with regard to SST. We also propose a new proactive protocol named the New Optimal Proactive Protocol (NOPP) based on an optimal scheduling of video segments on streaming-channel. SASST and NOPP are to be used in cloud and CDN (content delivery network) networks where the IP multicast or multicast HTTP on QUIC could be enabled, as their key principle is to allow the sharing of ongoing streams among clients requesting the same video content. Thus, clients and servers are often services running on virtual machines or in containers belonging to the same cloud or CDN infrastructure.


First Monday ◽  
2021 ◽  
Author(s):  
Yulia Belinskaya ◽  
Joan Ramon Rodriguez-Amat

Government’s domestic lockdown measures aimed at preventing the spread of COVID-19 during 2020 altered the patterns of media consumption, and massively boosted the traffic on video-streaming services including porn sites. This research explores the impact of COVID-19 on PornHub in three ways: video content, conditions of production, and related users’ activity. The analysis of a sample of 286 videos within a cluster of thematically relevant tags shows that what appears to be an emerging genre of COVID-19 porn is only a reshuffle of previously consolidated genres scaffolding its symbolic background. The analysis also shows that among the explicit sexual practices, some videos include pedagogical and humoristic insights. These apparently off-topic videos show societal and awareness-raising purposes. This article argues that the capacities of the PornHub interface enable social interactions that transcend the strictly sexual encounter, thus showing a form of social community of practice.


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