An evaluation of dynamic adaptive streaming over HTTP in vehicular environments

Müller, Christopher; Lederer, Stefan; Timmerer, Christian

doi:10.1145/2151677.2151686

Cited by 235 publications

(175 citation statements)

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“…All these findings well aligned to our observations. In a third study, an evaluation of the changing network conditions in a vehicular environment is implemented [155]. The results show that Microsoft SS achieves the highest average bit-rate and the lowest amount of switching.…”

Section: Content Servermentioning

confidence: 99%

Computational Inference and Control of Quality in Multimedia Services

Menkovski

2015

Springer Theses

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Please check the document version of this publication:• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:www.tue.nl/taverne Take down policyIf you believe that this document breaches copyright please contact us at:openaccess@tue.nl providing details and we will investigate your claim. Copyright c 2013 by Vlado Menkovski All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means without the prior written consent of the author. Typeset using L A T E X, printed in The NetherlandsTo my parents, Angel who dedicated his life to his sons and Snežana whose strength inspires me deeply. SummaryQuality is the degree of excellence we expect of a service or a product. It is also one of the key factors that determine its value. For multimedia services, understanding the experienced quality means understanding how the delivered fidelity, precision and reliability correspond to the users' expectations. Yet the quality of multimedia services is inextricably linked to the underlying technology. It is developments in video recording, compression and transport as well as display technologies that enables high quality multimedia services to become ubiquitous. The constant evolution of these technologies delivers a steady increase in performance, but also a growing level of complexity. As new technologies stack on top of each other the interactions between them and their components become more intricate and obscure. In this environment optimizing the delivered quality of multimedia services becomes increasingly challenging. The factors that affect the experienced quality, or Quality of Experience (QoE), tend to have complex non-linear relat...

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Section: Content Servermentioning

confidence: 99%

Computational Inference and Control of Quality in Multimedia Services

Menkovski

2015

Springer Theses

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“…By classifying the data with respect to the transport-level protocol only (i.e., TCP and UDP, used for applications needing or not, respectively, flow control and packet retransmissions upon loss, so roughly corresponding to non-interactive and interactive real-time services), we find out that TCP based applications are much more used than UDP ones (i.e., 97% of the traffic is TCP-based whilst only 3% is UDP based). It is worth noting that video streaming applications are nowadays mostly based on HTTP Live Streaming protocol (also known as HLS) [27]. Comparing users' demands separately instead of collectively, Figure 4 plots the user demand distribution given the 6-minute aggregation intervals (i.e., one cannot know through the data the instantaneous user demands because the collected data are aggregated as mentioned above).…”

Section: Data Consumption Characteristicsmentioning

confidence: 99%

Mobile data traffic offloading over Passpoint hotspots

et al. 2015

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Wi-Fi technology has always been an attractive solution for catering the increasing data demand in mobile networks because of the availability of WiFi networks, the high bit rates they provide, and the lower cost of ownership. However, the legacy WiFi technology lacks of seamless interworking between Wi-Fi and mobile cellular networks on the one hand, and between Wi-Fi hotspots on the other hand. Nowadays, the recently released Wi-Fi Certified Passpoint Program provides the necessary control-plane for these operations. Service providers can henceforth look to such Wi-Fi systems as a viable way to seamlessly offload mobile traffic and deliver added-value services, so that subscribers no longer face the frustration and aggravation of connecting to Wi-Fi hotspots. However, the technology being rather recent, we are not aware of public studies at the state of the art documenting the achievable gain in real mobile networks. In this paper, we evaluate the capacity and energy saving gain that one can get by offloading cellular data traffic over Passpoint hotspots as a function of different hotspot placement schemes and of access point selection policies (two enabled by the Passpoint control-plane and one independent of it). We compare the policies using real mobile data from the Orange network in Paris. We show that offloading using Passpoint control-plane information can grant up to 15% capacity gain and 13% energy saving gain with respect to Passpoint-agnostic ones based on signal quality information. As of placement strategy, installing Passpoint hotspots in the outer annulus of the macrocell coverage grants the maximum capacity gain.

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“…First, the video level v n is selected as the center element ofṼ, that offers the smallest absolute difference to T among the video levels in V (line 5). The algorithm selects the remaining video levels by choosing L−1 video levels around v n (line [6][7][8][9][10][11][12][13][14]. If L is an odd number, a symmetric selection is conducted (line 12).…”

Section: Network-aware Video Level Selectionmentioning

confidence: 99%

“…Nevertheless, due to its favorable deployment and transport characteristics, AHS offers major advantages compared to other systems for uplink streaming. One option to reduce the computational demand is to use scalable video coding with AHS [9], but it is still not clear whether the scalable extensions of modern codecs, such as H.264/AVC and H.265/HEVC, will find broad acceptance in the market.…”

Section: Introductionmentioning

confidence: 99%

Network-aware video level encoding for uplink adaptive HTTP streaming

Lottermann

Gül

Schroeder³

et al. 2015

2015 IEEE International Conference on Communications (ICC)

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Abstract-We study the uplink delivery of live video using adaptive HTTP streaming (AHS). In AHS, the process of simultaneously creating video levels at different rates is computationally demanding and quickly exceeds the computational capacity of mobile devices. As a remedy, we propose a network-aware video level selection approach which reduces the number of levels that need to be encoded. To this end, we develop an algorithm which selects a reduced set of video levels from a static pre-defined set based on TCP uplink throughput information. More specifically, during session start-up and after inter-RAN handovers, TCP uplink throughput information from a remote database is used while otherwise, actual TCP uplink throughput measurements are performed. We test the proposed approach in an automotive scenario to upstream the video of a vehicle's front-facing camera to a remote video portal. Our results show that our proposed network-aware video level selection approach leads to a significant reduction of the number of video levels that need to be encoded. At the same time, a similar quality of experience is achieved in terms of mean subjective quality of the delivered video segments, interrupted playback duration due to stalling events, and number of quality switches when compared to an implementation which considers the static full set of video levels.

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An evaluation of dynamic adaptive streaming over HTTP in vehicular environments

Cited by 235 publications

References 10 publications

Computational Inference and Control of Quality in Multimedia Services

Computational Inference and Control of Quality in Multimedia Services

Mobile data traffic offloading over Passpoint hotspots

Network-aware video level encoding for uplink adaptive HTTP streaming

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