NetTube: Exploring Social Networks for Peer-to-Peer Short Video Sharing

Cheng, Xu; Liu, J.

doi:10.1109/infcom.2009.5062028

Cited by 115 publications

(84 citation statements)

References 19 publications

(20 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…We show that our model is consistent with empirically observed properties of request patterns in such VoD services [5,6,16,29]. A limitation of this model is that it imposes the constraint that the recommendations are symmetric (i.e., Video A recommends Video B implies Video B recommends Video A).…”

Section: Contributionssupporting

confidence: 78%

See 1 more Smart Citation

Request patterns and caching for VoD services with recommendation systems

Gupta¹,

Moharir²

2017

2017 9th International Conference on Communication Systems and Networks (COMSNETS)

View full text Add to dashboard Cite

Abstract. Video on Demand (VoD) services like Netflix and YouTube account for ever increasing fractions of Internet traffic. It is estimated that this fraction will cross 80% in the next three years. Most popular VoD services have recommendation engines which recommend videos to users based on their viewing history, thus introducing time-correlation in user requests. Understanding and modeling this time-correlation in user requests is critical for network traffic engineering. The primary goal of this work is to use empirically observed properties of user requests to model the effect of recommendation engines on request patterns in VoD services. We propose a Markovian request model to capture the timecorrelation in user requests and show that our model is consistent with the observations of existing empirical studies. Most large-scale VoD services deliver content to users via a distributed network of servers as serving users requests via geographically co-located servers reduces latency and network bandwidth consumption. The content replication policy, i.e., determining which contents to cache on the servers is a key resource allocation problem for VoD services. Recent studies show that low start-up delay is a key Quality of Service (QoS) requirement of users of VoD services. This motivates the need to prefetch (fetch before contents are requested) and cache content likely to be requested in the near future. Since pre-fetching leads to an increase in the network bandwidth usage, we use our Markovian model to explore the trade-offs and feasibility of implementing recommendation based prefetching.

show abstract

Section: Contributionssupporting

confidence: 78%

“…Empirical studies have concluded that content popularity for VoD services with recommendation systems, e.g., YouTube, can be well-fitted with the Zipf distribution for the popular videos and popularity for the less popular videos decreases faster than the rate predicted by the Zipf distribution [6].…”

Section: Small-world Recommendation Graphmentioning

confidence: 99%

Request patterns and caching for VoD services with recommendation systems

Gupta¹,

Moharir²

2017

2017 9th International Conference on Communication Systems and Networks (COMSNETS)

View full text Add to dashboard Cite

show abstract

“…The interesting observations among the many include 1) a clear power-law distribution for the popular videos, 2) a small world phenomenon for the videos linked by internal related video links, and 3) as these sites undertake videos which have a much higher demand on the bandwidth, a peer-to-peer structure is discussed. Indeed, NetTube is developed showing the possibility of using a peer-to-peer in [4].…”

Section: Related Workmentioning

confidence: 99%

Understanding the External Links of Video Sharing Sites: Measurement and Analysis

Lai

Wang

2013

IEEE Trans. Multimedia

View full text Add to dashboard Cite

Recently, many video sharing sites provide external links so that their video or audio contents can be embedded into external web sites. For example, users can copy the embedded URLs of the videos of YouTube and post on their own blogs. Clearly, the purpose of such functionality is to increase the distribution of the videos and the associated advertisement. In this paper, we provide a comprehensive measurement study and analysis on these external links. With the traces collected from two major VOD sites, YouTube and Youku of China, we show that the external links have various impact on the popularity of the VOD sites. More specifically, for videos that have been uploaded for eight months in Youku, around 15% of views can come from external links. Some contents are densely linked, for example, the comedy videos can attract more than 800 external links on average. We also study the relationship between the external links and the internal links. We show that there are correlations; for example, if a video is popular itself, it will likely have a larger number of external links. Another observation is that we always find that the external links of Youku usually have a higher impact than that of YouTube. We conjecture that a more regional site may enjoy a relatively higher impact from the external links.

show abstract

“…Minimizing energy consumption during prefetching is critical for mobiles -studies [6,11] indicate that WiFi is typically more efficient than cellular networks, and techniques to aggregate multiple data transfers to save energy have been developed. [8,17] exploit social networks to assist prefetching video prefixes. In general, prefetching has been explored in client-server and peer-to-peer settings using factors such as energy, transfer volume and user preferences.…”

Section: Algorithm 1 Prefetch Schedulingmentioning

confidence: 99%

O 2 SM: Enabling Efficient Offline Access to Online Social Media and Social Networks

et al. 2013

View full text Add to dashboard Cite

Abstract. In this paper, we consider the problem of efficient social media access on mobile devices, and propose an Offline Online Social Media (O 2 SM) Middleware to: (i) rank the social media streams based the probability that a given user views a given content item, and (ii) invest the limited resources (network, energy, and storage) on prefetching only those social media streams that are most likely to be watched when mobile devices have good Internet connectivity. The ranking scheme leverages social network information to drive a logistic regression based technique that is subsequently exploited to design an utility based content prefetching mechanism. We implemented O 2 SM and a corresponding app, oFacebook, on Android platforms. We evaluated O 2 SM via trace data gathered from a user study with real world users executing oFacebook. Our experimental results indicate that O 2 SM exhibits superior viewing performance and energy efficiency for mobile social media apps; its lightweight nature makes it easily deployable on mobile platforms.

show abstract

NetTube: Exploring Social Networks for Peer-to-Peer Short Video Sharing

Cited by 115 publications

References 19 publications

Request patterns and caching for VoD services with recommendation systems

Request patterns and caching for VoD services with recommendation systems

Understanding the External Links of Video Sharing Sites: Measurement and Analysis

O 2 SM: Enabling Efficient Offline Access to Online Social Media and Social Networks

Contact Info

Product

Resources

About