Quality Adaptation in P2P Video Streaming Based on Objective QoE Metrics

Rückert, Julius; Abboud, Osama; Zinner, Thomas; Steinmetz, Ralf; Hausheer, David

doi:10.1007/978-3-642-30054-7_1

Cited by 19 publications

(11 citation statements)

References 21 publications

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“…The authors propose a two-stage adaptation mechanism for heterogeneous clients and show that stalling events can be reduced and even avoided by reducing the video quality at the clients in a controlled manner. The approach was further extended by [11] to also take different QoE aspects into consideration in the adaptation process. While these mechanisms were proposed for mesh-pull based VoD streaming scenarios, the work presented herein aims at live streaming using hybrid streaming topologies and push and pull based delivery mechanisms at the same time, which requires a significantly different algorithmic design.…”

Section: Related Workmentioning

confidence: 99%

How to adapt: SVC-based quality adaptation for hybrid peercasting systems

Wichtlhuber

Rückert

Winter

et al. 2015

2015 IFIP/IEEE International Symposium on Integrated Network Management (IM)

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Live streaming of large-scale events such as the Olympic Games with a huge number of viewers is challenging, as the streaming infrastructure needs to scale fast and big, and often in an unpredictable manner. Peer-to-peer (P2P) live streaming (Peercasting) has proven to be beneficial in these scenarios, as resources are scaling inherently with the number of nodes. However, churn behavior in a node's neighborhood may result in fluctuating downstream bandwidth and thus freezing (stalling) playback. Related work tries to mitigate this effect by using layered video codecs, focusing on single-dimensional scalability in mesh-pull based systems. Yet, the benefits of multidimensional scalability (resolution, frame rate, and quantization) combined with coexisting pull-/push mechanisms introduced by modern hybrid P2P streaming architectures have not been studied in detail. Consequently, this work proposes a new scheduling algorithm taking these aspects into account. The evaluation shows large benefits for end-users by reducing the frequency of stalls by 90% even under extreme conditions.

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Section: Related Workmentioning

confidence: 99%

How to adapt: SVC-based quality adaptation for hybrid peercasting systems

Wichtlhuber

Rückert

Winter

et al. 2015

2015 IFIP/IEEE International Symposium on Integrated Network Management (IM)

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“…Rückert et al used VQM scores to optimize the Scalable Video Coding (SVC) [23] video quality according to user perception, reducing up to 60% bandwidth required to stream video in P2P-based video on demand system [22]. Their proposed optimization sets the layer that maximizes perceptual video quality as the target optimization layer.…”

Section: Related Workmentioning

confidence: 99%

QoE-aware optimization for video delivery and storage

Devlić

Kamaraju

Lungaro

et al. 2015

2015 IEEE 16th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)

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QoE-aware optimization for video delivery and storage. In: 2015 IEEE 16th International Symposium on "A World of Wireless, Mobile and MultimediaNetworks" (WoWMoM) 2015 (pp. 1-10 Abstract-The explosive growth of Over-the-top (OTT) online video strains capacity of operators' networks, which severely threatens video quality perceived by end users. Since video is very bandwidth consuming, its distribution costs are becoming too high to scale with network investments that are required to support the increasing bandwidth demand. Content providers and operators are searching for solutions to reduce this video traffic load, without degrading their customers' perceived Quality of Experience (QoE). This paper proposes a method that can programmatically optimize video content for desired QoE according to perceptual video quality and device display properties, while achieving bandwidth and storage savings for content providers, operators, and end users. The preliminary results obtained with Samsung Galaxy S3 phone show that up to 60% savings can be achieved by optimizing movies without compromising the perceptible video quality, and up to 70% for perceptible, but not annoying video quality difference. Tailoring video optimization to individual user perception can provide seamless QoE delivery across all users, with a low overhead (i.e., 10%) required to achieve this goal. Finally, two applications of video optimization: QoE-aware delivery and storage, are proposed and examined.

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“…The main differences of flows and requests are illustrated in Figure 2. TRANSIT uses the Scalable Video Codec (SVC) [19] extension of the H.264/AVC [22] video standard, which was shown to be beneficial for supporting peers with heterogeneous resources in [1], [16]. SVC-encoded content can be decoded at different quality layers, where only parts of the full bit stream are needed to decode the video at a lower quality.…”

Section: A Transit Designmentioning

confidence: 99%

TRANSIT: Supporting transitions in Peer-to-Peer live video streaming

Wichtlhuber

Richerzhagen

Rückert

et al. 2014

2014 IFIP Networking Conference

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Abstract-The transmission of video content accounts for a large share of today's Internet traffic. While Video-on-Demand (VoD) substantially contributes to this, live streaming events such as video broadcasts from the Olympic Games can cause very high traffic volumes in the short term as well. Such peaks along with high fluctuations triggered by sudden changes in the behavior of users make the design of live streaming systems particularly challenging. Peer-to-Peer (P2P) has proven to be a scalable approach for disseminating content to a large number of users. Accordingly, the body of research offers numerous P2P live streaming approaches tailored towards specific scenarios and assumptions. However, no single approach is able to perform well under all possible conditions. Keeping up a high performance when conditions are changing is a challenge, since topology management and scheduling mechanisms cannot be exchanged easily. Therefore, this paper proposes TRANSIT, a new approach going beyond existing works in that it supports transitions between different live streaming mechanisms. TRANSIT makes different configurations of such mechanisms seamlessly exchangeable to enable the optimal choice of configurations for a wide range of live streaming scenarios. The approach is evaluated using measurement-and trace-based workloads. The results show that TRANSIT is able to maintain a high performance at a low overhead in highly fluctuating environments, whereas static configurations show serious performance degradations.

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Quality Adaptation in P2P Video Streaming Based on Objective QoE Metrics

Cited by 19 publications

References 21 publications

How to adapt: SVC-based quality adaptation for hybrid peercasting systems

How to adapt: SVC-based quality adaptation for hybrid peercasting systems

QoE-aware optimization for video delivery and storage

TRANSIT: Supporting transitions in Peer-to-Peer live video streaming

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