Adaptation logic for HTTP dynamic adaptive streaming using geo-predictive crowdsourcing for mobile users

Dubin, Ran; Dvir, Amit; Pele, Ofir; Hadar, Ofer; Katz, Itay; Mashiach, Ori

doi:10.1007/s00530-016-0525-6

Cited by 14 publications

(5 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While Ookla has open-sourced some of its data, it is hard to get a reliable live estimate of the experienced bandwidth. Dubin, et al [7] propose using crowd-sourced bandwidth information from a dataset provided by Wefi Ltd to adapt video bitrates for on-demand streaming. While the dataset accounts for spatiotemporal variations in bandwidth, it is difficult to track real time variations in expected bandwidth.…”

Section: Related Workmentioning

confidence: 99%

Foresight

Sethuraman

Sarma

Dhekne

et al. 2021

Proceedings of the 12th ACM Multimedia Systems Conference

View full text Add to dashboard Cite

The paper develops Foresight to provide an up-to-date improvement of earlier ideas for the prediction of bandwidth availability for arbitrary applications on mobile devices, based on CRUSP's crowdsourced reporting to a geographical database and application-independent querying by mobile devices. The paper uses video streaming as an example and comprises an actual implementation using a video player based on ExoPlayer.

show abstract

Section: Related Workmentioning

confidence: 99%

Foresight

Sethuraman

Sarma

Dhekne

et al. 2021

Proceedings of the 12th ACM Multimedia Systems Conference

View full text Add to dashboard Cite

show abstract

“…It might result in incorrectness prediction results. On the another hand, geo-predictive crowdsourcing [19] has an approach on clients' previous download experience. Their crowdsourcing-based algorithms outperformed all other methods regarding QoS.…”

Section: Related Workmentioning

confidence: 99%

A Fuzzy-Based Adaptive Streaming Algorithm for Reducing Entropy Rate of DASH Bitrate Fluctuation to Improve Mobile Quality of Service

Van

Park

Nam

et al. 2017

Entropy

View full text Add to dashboard Cite

Dynamic adaptive streaming over Hypertext Transfer Protocol (HTTP) is an advanced technology in video streaming to deal with the uncertainty of network states. However, this technology has one drawback as the network states frequently and continuously change. The quality of a video streaming fluctuates along with the network changes, and it might reduce the quality of service. In recent years, many researchers have proposed several adaptive streaming algorithms to reduce such changes. However, these algorithms only consider the current state of a network. Thus, these algorithms might result in inaccurate estimates of a video quality in the near term. Therefore, in this paper, we propose a method using fuzzy logic and a mathematics moving average technique, in order to reduce mobile video quality fluctuation in Dynamic Adaptive Streaming over HTTP (DASH). First, we calculate the moving average of the bandwidth and buffer values for a given period. On the basis of differences between real and average values, we propose a fuzzy logic system to deduce the value of the video quality representation for the next request. In addition, we use the entropy rate of a bandwidth measurement sequence to measure the predictable/stabilization of our method. The experiment results show that our proposed method reduces video quality fluctuation as well as improves 40% of bandwidth utilization compared to existing methods.

show abstract

“…Recently DASH (dynamic adaptation streaming over HTTP (i.e., HyperText Transfer Protocol))-based technology has been widely adopted to deliver video content over the Internet since it is able to automatically match video quality with the available network bandwidth for proper accessibility and delivery [1]. Based on DASH system architecture as shown in Figure 1, the video on the server side is divided into small segments with different representation levels, all of which are described in an MPD (media presentation description) file [2].…”

Section: Introductionmentioning

confidence: 99%

VCC-DASH: A Video Content Complexity-Aware DASH Bitrate Adaptation Strategy

Duan¹,

Zhang²,

Wang³

et al. 2020

Electronics

View full text Add to dashboard Cite

Traditional DASH (dynamic adaptation streaming over HTTP(i.e., HyperText Transfer Protocol)) bitrate strategy cannot differentiate segments with different complexities of video content, resulting in the user’s QoE (quality of experience) of segments with high content complexity as worse than that with low content complexity. In case of this, this paper firstly studies video coding and puts forward the definition of video content complexity. Then the effects of content complexity on user’s QoE is analyzed and the QoE utility function of the segment is formulated based on its MOS (mean opinion score, related to the content complexity and bitrate) and bitrate switching between consecutive segments. Last, in order to maximize user’s QoE, this paper proposes VCC-DASH (video content complexity-aware DASH bitrate adaptation strategy) under the constraints of the network bandwidth and the buffer occupancy. In simulations, we compare VCC-DASH with the classical bitrate adaptation strategy proposed by Liu et al. (LIU’s strategy, for short). The simulation results show that the two strategies have similar performances in bitrate switching numbers, playback interruption times, and buffer lengths. In addition, it is more important for simulation results to reveal that VCC-DASH’s average bitrate is much higher than that of LIU’s strategy, which means that VCC-DASH can make fuller use of the network bandwidth than LIU’s strategy does. Moreover, the MOS distribution of the VCC-DASH is more concentrated on the better scores “4~5”, which profit from its content complexity-aware adaptation to allocate more bandwidth resources to high-complexity segments.

show abstract

Adaptation logic for HTTP dynamic adaptive streaming using geo-predictive crowdsourcing for mobile users

Cited by 14 publications

References 35 publications

Foresight

Foresight

A Fuzzy-Based Adaptive Streaming Algorithm for Reducing Entropy Rate of DASH Bitrate Fluctuation to Improve Mobile Quality of Service

VCC-DASH: A Video Content Complexity-Aware DASH Bitrate Adaptation Strategy

Contact Info

Product

Resources

About