Available Bandwidth Estimation for Adaptive Video Streaming in Mobile Ad Hoc

Castellanos, Wilder E.; Guerri, Juan Carlos; Arce, Pau

doi:10.1007/s10776-019-00431-0

Cited by 9 publications

(5 citation statements)

References 34 publications

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“…We also note that other bandwidth measurement methods exist, including the traditional active probing methods such as packet pair/train dispersion probing that is often used to estimate the end-to-end capacity of a network path [18], [142], and Will's simple sideload (WSSL) method, which retrieves a fully available object (such as a previous segment) along with the live-edge segment for bandwidth measurement purposes [31]. However, active probing methods may be less desirable in media streaming applications as these methods introduce additional traffic to the network (which already is a scarce resource in streaming) [37]. They are often not well-adapted to handle streaming traffic's periodic and bursty nature, either [173].…”

Section: Media Over Quic (Moq)mentioning

confidence: 99%

Catching the Moment With LoL$^+$ in Twitch-Like Low-Latency Live Streaming Platforms

Bentaleb

Akcay

Lim

et al. 2022

IEEE Trans. Multimedia

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Our earlier Low-on-Latency (dubbed as LoL) solution offered an accurate bandwidth prediction and rate adaptation algorithm tailored for live streaming applications that targeted an end-to-end latency of up to two seconds. While LoL was a significant step forward in multi-bitrate low-latency live streaming, further experimentation and testing showed that there was room for improvement in three areas. First, LoL used hardcoded parameters computed from an offline training process in the rate adaptation algorithm and this was seen as a significant barrier in LoL's wide deployment. Second, LoL's objective was to maximize a collective QoE function. Yet, certain use cases have specific objectives besides the singular QoE and this had to be accommodated. Third, the adaptive playback speed control failed to produce satisfying results in some scenarios. Our goal in this paper is to address these areas and make LoL sufficiently robust to deploy. We refer to the enhanced solution as LoL + , which has been integrated to the official dash.js player in v3.2.0.

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Section: Media Over Quic (Moq)mentioning

confidence: 99%

Catching the Moment With LoL$^+$ in Twitch-Like Low-Latency Live Streaming Platforms

Bentaleb

Akcay

Lim

et al. 2022

IEEE Trans. Multimedia

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“…Most of the aforesaid techniques have been designed for classic wired networks. The rise of wireless networks and complex network infrastructures have fostered the development of available bandwidth estimation approaches, e.g., for 3G/4G networks [16], cloud networks [17], ad-hoc networks [18,19], or Software Defined Networking (SDN) networks [20]. The advent of these new tools has motivated some studies, such as [21] to propose an updated summary of the metrics, characteristics, and techniques related to the measurement of the available bandwidth.…”

Section: State Of the Artmentioning

confidence: 99%

FAM: A frame aggregation based method to infer the load level in IEEE 802.11 networks

Bouzouita

Busson

Rivano

2022

Computer Communications

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“…Therefore, algorithms for estimation of available resources, for example in terms of available bandwidth, have to be implemented. Some estimation mechanisms proposed can be consulted in (Castellanos, Guerri, & Arce, 2019;Chaudhari & Biradar, 2015).…”

Section: Constant Emission Rate Available Videomentioning

confidence: 99%

Advanced techniques for adaptive video streaming in SDNs

Castellanos,

Bustos,

Sanabria

2021

Preprint

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In the coming years a new management model of telecommunication networks will begin to be implemented. This model, known as Software Defined Networks, implies a radical change in the way networks are conceived today. Therefore, it is necessary to develop studies that allow to know this scenario and its implications during the transmission of different types of traffic. Especially, it is important to analyze the behavior of video traffic due to the significant increase of these flows through networks as well as to the massive use of new video services with ultra-high resolution formats. This fact also implies an enormous consumption of network resources like bandwidth. Likewise, the likelihood to impact on other traffic flows that coexist in the same network is increased caused by network congestion. Under these conditions the ability to adapt the video streams to the available resources of the network is an essential requirement in modern video services in order to prevent network congestion. Therefore, adaptive techniques for video transmission have become an important area of interest for researchers, technology providers and network operators.This chapter briefly describes a study on software-defined networks and the tools necessary for video transmission on this type of networks. Among the aspects presented is the methodology used to establish the video transmission and the procedure to evaluate the quality obtained. A video transmission experiment is presented, which consists on the evaluation of adaptive transmission of video streams using adaptive techniques as MPEG/DASH and scalable coding. The experiments were carried out over a software-defined network topology in the MININET platform.

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Available Bandwidth Estimation for Adaptive Video Streaming in Mobile Ad Hoc

Cited by 9 publications

References 34 publications

Catching the Moment With LoL$^+$ in Twitch-Like Low-Latency Live Streaming Platforms

Catching the Moment With LoL$^+$ in Twitch-Like Low-Latency Live Streaming Platforms

FAM: A frame aggregation based method to infer the load level in IEEE 802.11 networks

Advanced techniques for adaptive video streaming in SDNs

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