Adaptive video streaming for mobile clients

Brandt, Jens; Wolf, Lars

doi:10.1145/1496046.1496074

Cited by 8 publications

(4 citation statements)

References 1 publication

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“…An example of the research work for cloud gaming services can be seen in [5], where the H.264 video encoding parameter was adjusted to match for the client device capability. More examples [6][7][8] can be found in the field of video-on-demand. DOI: 10.5176/2251-3043_4.2.318…”

Section: Background and Related Workmentioning

confidence: 99%

Hybrid Method for Adaptive Cloud Gaming Contents

Jitpukdeebodintra

Witosurapot

2015

GSTF J Comput

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Abstract-Methods for adapting cloud gaming content can be divided according to client-or server-returned benefits. In this paper, we argue that the better method should be performed in such a way that both client and server should share common benefits. By working on a cooperative scheme, the basic of trans-rendering and trans-scaling mechanism are proposed to work together for obtaining better utilizations of network bandwidth and graphic processor altogether. Based on our experiments of running cloud gaming services in simulated environment, we show many evidences that significantly improved benefits can be obtained as planned. Our proposed hybrid adaptation method is therefore clearly helpful for the game research community.

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Section: Background and Related Workmentioning

confidence: 99%

Hybrid Method for Adaptive Cloud Gaming Contents

Jitpukdeebodintra

Witosurapot

2015

GSTF J Comput

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“…Existing systems often monitor the observed throughput, but foreseeing future degradations or even connectivity loss is hard. To better enable the streaming application to predict future bandwidth availability and then adapt the video quality, regardless of whether adaptation is performed using a scalable codec [Huang et al 2003;Schierl et al 2010], transcoding [Brandt and Wolf 2008] or multi-quality segments [Pantos et al 2010;Zambelli 2009;Adobe 2010;Move Networks 2008], we propose to use a GPS-based bandwidth lookup service with a predictive video quality selection algorithm, i.e., similar to have been done by Wac et al [2006b], but in a completely different application scenario.…”

Section: Related Workmentioning

confidence: 99%

Video streaming using a location-based bandwidth-lookup service for bitrate planning

Riiser¹,

Endestad²,

Vigmostad³

et al. 2012

ACM Trans. Multimedia Comput. Commun. Appl.

120

106

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A lot of people around the world commute using public transportation and would like to spend this time viewing streamed video content such as news or sports updates. However, mobile wireless networks typically suffer from severe bandwidth fluctuations, and the networks are often completely unresponsive for several seconds, sometimes minutes. Today, there are several ways of adapting the video bitrate and thus the video quality to such fluctuations, e.g., using scalable video codecs or segmented adaptive HTTP streaming that switches between non-scalable video streams encoded in different bitrates. Still, for a better long-term video playout experience that avoids disruptions and frequent quality changes while using existing video adaptation technology, it is desirable to perform bandwidth prediction and planned quality adaptation. This paper describes a video streaming system for receivers equipped with a GPS. A receiver's download rate is constantly monitored, and periodically reported back to a central database along with associated GPS positional data. Thus, based on the current location, a streaming device can use a GPS-based bandwidth-lookup service in order to better predict the near-future bandwidth availability and create a schedule for the video playout that takes likely future availability into account. To create a prototype and perform initial tests, we conducted several field trials while commuting using public transportation. We show how our database has been used to predict bandwidth fluctuations and network outages, and how this information helps maintain uninterrupted playback with less compromise on video quality than possible without prediction.

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“…In contrast to adaptive streaming techniques, where the video stream is adapted to the client after its creation, e.g. during transmission [6], in the Games@Large framework the visual output is already generated with respect to the clients capabilities. As each graphics command issued by the game passes through our proxy DLL library, the parameters are adapted to render images which are optimal for streaming to the corresponding client: for example the viewport is adapted to the client's screen size, so that no additional image adjustment besides video encoding is needed.…”

Section: Low Complexity H264 Video Encoding On Server-sidementioning

confidence: 99%

Accelerated video streaming for gaming architecture

Laikari

Fechteler

Prestele

et al. 2010

2010 3dtv-Conference: The True Vision - Capture, Transmission and Display of 3D Video

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Computer game processing requirements for the CPU and graphics performance are growing all the time higher. At the same time many low cost and modest performance CE devices are gaining popularity. People are already used to mobile life style inside home and on the go and they want to enjoy entertainment everywhere. This paper describes an accelerated video streaming method used in a gaming system, called Games@Large, which enables heavy PC game playing on low cost CE devices without the need of game software modification. The key innovations of the Games@Large system are game execution distribution, game streaming, including graphics/video and audio streaming and game control decentralization as well as network quality of service management. This paper concentrates on the advanced video streaming techniques used in Games@Large.

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Adaptive video streaming for mobile clients

Cited by 8 publications

References 1 publication

Hybrid Method for Adaptive Cloud Gaming Contents

Hybrid Method for Adaptive Cloud Gaming Contents

Video streaming using a location-based bandwidth-lookup service for bitrate planning

Accelerated video streaming for gaming architecture

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