Progressive Download for 3G Wireless Multicasting

Yetgin, Zeki; Seckin, Gamze

doi:10.1109/fgcn.2007.186

Cited by 7 publications

(4 citation statements)

References 11 publications

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“…We evaluated the performance of the proposed scheme by comparing its results with those of the progressive download scheme that transmits the whole video file to the member device [19, 37]. As discussed in the subsection “Architecture and Implementation”, we implemented a video streaming relay scheme on an Android device for the performance evaluation.…”

Section: Performance Evaluationmentioning

confidence: 99%

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Scalable Video Streaming Relay for Smart Mobile Devices in Wireless Networks

Kwon

Je²,

Kim

et al. 2016

PLoS ONE

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Recently, smart mobile devices and wireless communication technologies such as WiFi, third generation (3G), and long-term evolution (LTE) have been rapidly deployed. Many smart mobile device users can access the Internet wirelessly, which has increased mobile traffic. In 2014, more than half of the mobile traffic around the world was devoted to satisfying the increased demand for the video streaming. In this paper, we propose a scalable video streaming relay scheme. Because many collisions degrade the scalability of video streaming, we first separate networks to prevent excessive contention between devices. In addition, the member device controls the video download rate in order to adapt to video playback. If the data are sufficiently buffered, the member device stops the download. If not, it requests additional video data. We implemented apps to evaluate the proposed scheme and conducted experiments with smart mobile devices. The results showed that our scheme improves the scalability of video streaming in a wireless local area network (WLAN).

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Section: Performance Evaluationmentioning

confidence: 99%

“…We compared the results to those of the progressive download scheme, which has already been implemented in many streaming services [37]. Fig 14 shows the average number of playback interruptions of the member devices.…”

Section: Performance Evaluationmentioning

confidence: 99%

Scalable Video Streaming Relay for Smart Mobile Devices in Wireless Networks

Kwon

Je²,

Kim

et al. 2016

PLoS ONE

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“…A standard web server delivers a video file over HTTP (progressive download), while a streaming server opens a conversation with the local machine. In order to maintain the various mobile device platforms, we choose HTTP progressive download as the delivery method for videos [9][10].…”

Section: A Video Sharing Systemmentioning

confidence: 99%

S-LRU: A cache replacement algorithm of video sharing system for mobile devices

Liu

Chen

Sun

2012

Proceedings of 2012 2nd International Conference on Computer Science and Network Technology

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Video sharing system for mobile devices is an important mobile service which can be used to share videos with others. Scalability is critical to the system. Cache technology, which employs cache servers to offload the original server, has been proposed to attack the scalability problem. Traditional replacement algorithms for cache technology are not suitable for the video sharing system. In this paper, we proposed a cache replacement algorithm called S-LRU for the system. In S-LRU, we consider the size difference of videos. Experimental results demonstrate that S-LRU outperforms the other algorithms.

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“…For example, a concept called "adaptive streaming" is applied to progressive download in [14], [15], in which the quality of a pre-recorded video content shifts as link qualities change. The performance of multicasting in a 3G system are tackled in [16], where the authors conclude that the "multimedia broadcast multicast system" specified in 3GPP improves the experience of users over traditional download mechanisms in a multicast scenario. While these works are tangential to our own, our model could be generalized to include the concept of adaptive streaming as part of the decision process.…”

Section: Related Workmentioning

confidence: 99%

Network-congestion-aware video streaming: A rest-and-download approach

Jung

Gupta

Mastronarde

et al. 2012

2012 9th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON)

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Abstract-On-demand video services such as Youtube and Hulu are expected to comprise a large percentage of the increasing data loads in mobile networks. On-demand video is distinctive because it is pre-recorded and therefore can be considered elastic traffic because the video frame buffer can be downloaded well past the current point of playback. Based on this observation, we propose Video Rest-and-Download (VR&D) as a video download application framework that aims to reduce network congestion while maintaining playback quality. The intuition for VR&D is that, in a scenario where radio resources are shared by multiple data users, the video user can "rest" for some amount of time until fewer users are in the network, thereby allowing other data users to complete their downloads faster, without affecting playback quality. We present an algorithmic framework for VR&D based on the Markov Decision Process that uses the history and current state of network activity to determine how aggressive the user should be in downloading video frames. We evaluate its performance using a simulated UMTS network with HSDPA data service based on real network traces from a major U.S. carrier. Our results show that, compared to the existing solution, during the time of video playback this application can reduce download time by as high as 50%, and alleviate network congestion by up to 30% with minimal effect on playback quality.

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Progressive Download for 3G Wireless Multicasting

Cited by 7 publications

References 11 publications

Scalable Video Streaming Relay for Smart Mobile Devices in Wireless Networks

Scalable Video Streaming Relay for Smart Mobile Devices in Wireless Networks

S-LRU: A cache replacement algorithm of video sharing system for mobile devices

Network-congestion-aware video streaming: A rest-and-download approach

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