On-the-Fly Erasure Coding for Real-Time Video Applications

Tournoux, P; Lochin, Emmanuel; Lacan, Jérôme; Bouabdallah, Amine; Roca, Vincent

doi:10.1109/tmm.2011.2126564

Cited by 43 publications

(48 citation statements)

References 32 publications

(63 reference statements)

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“…However, this problem is computationally intractable for three or more receivers and hence only a heuristic solution is presented. The delay benefits of a RLC based scheme have been examined in [21], where repair packets are generated on-the-fly through RLC according to feedback messages that are periodically received by the servers. This scheme copes efficiently with the packet erasures and is appropriate for real-time sources such as video.…”

Section: Related Workmentioning

confidence: 99%

Adaptive Prioritized Random Linear Coding and Scheduling for Layered Data Delivery From Multiple Servers

Thomos

Kurdoglu²,

Frossard

et al. 2015

IEEE Trans. Multimedia

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In this paper, we deal with the problem of jointly determining the optimal coding strategy and the scheduling decisions when receivers obtain layered data from multiple servers. The layered data is encoded by means of Prioritized Random Linear Coding (PRLC) in order to be resilient to channel loss while respecting the unequal levels of importance in the data, and data blocks are transmitted simultaneously in order to reduce decoding delays and improve the delivery performance. We formulate the optimal coding and scheduling decisions problem in our novel framework with the help of Markov Decision Processes (MDP), which are effective tools for modeling adapting streaming systems. Reinforcement learning approaches are then proposed to derive reduced computational complexity solutions to the adaptive coding and scheduling problems. The novel reinforcement learning approaches and the MDP solution are examined in an illustrative example for scalable video transmission. Our methods offer large performance gains over competing methods that deliver the data blocks sequentially. The experimental evaluation also shows that our novel algorithms offer continuous playback and guarantee small quality variations which is not the case for baseline solutions. Finally, our work highlights the N. Thomos is with the

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Section: Related Workmentioning

confidence: 99%

Adaptive Prioritized Random Linear Coding and Scheduling for Layered Data Delivery From Multiple Servers

Thomos

Kurdoglu²,

Frossard

et al. 2015

IEEE Trans. Multimedia

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“…To be specific, we need to evaluate P n ϒ 1:n (r,λ) and R n ϒ 1:n (r,λ) according to (32) and (33), for all choices of r andλ, and then remove the points not lying on the convex hull of these points.…”

Section: A Exact Constructionmentioning

confidence: 99%

“…According to (32) and (33), this P-R characteristic includes a set of scaled version of the P-R characteristic forH (i.e.…”

Section: A Exact Constructionmentioning

confidence: 99%

PET Protection Optimization for Streaming Scalable Videos With Multiple Transmissions

Xiong

Taubman

Sivaraman

2013

IEEE Trans. on Image Process.

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Abstract-This paper investigates priority encoding transmission (PET) protection for streaming scalably compressed video streams over erasure channels, for the scenarios where a small number of retransmissions are allowed. In principle, the optimal protection depends not only on the importance of each stream element, but also on the expected channel behavior. By formulating a collection of hypotheses concerning its own behavior in future transmissions, limited-retransmission PET (LR-PET) effectively constructs channel codes spanning multiple transmission slots and thus offers better protection efficiency than the original PET. As the number of transmission opportunities increases, the optimization for LR-PET becomes very challenging because the number of hypothetical retransmission paths increases exponentially. As a key contribution, this paper develops a method to derive the effective recovery-probability versus redundancy-rate characteristic for the LR-PET procedure with any number of transmission opportunities. This significantly accelerates the protection assignment procedure in the original LR-PET with only two transmissions, and also makes a quick and optimal protection assignment feasible for scenarios where more transmissions are possible. This paper also gives a concrete proof to the redundancy embedding property of the channel codes formed by LR-PET, which allows for a decoupled optimization for sequentially dependent source elements with convex utility-length characteristic. This essentially justifies the source-independent construction of the protection convex hull for LR-PET.

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“…The SGM has been widely used to evaluate application performance since early work used it to model loss processes seen on academic networks [16]. Recent evaluations of video streaming [15] and video quality estimation tools [13] have used SGM models.…”

Section: Modelling Residential Packet Lossmentioning

confidence: 99%

“…Previous studies have used Markov-chain models, such as the classical Gilbert model [3], to generate packet loss processes for evaluation of video streaming applications [15] and error repair [6]. More complex Markov-chain models [16], [5], and Hidden Markov Models (HMMs) [10], [11] have been proposed to describe packet loss on academic networks.…”

Section: Introductionmentioning

confidence: 99%

Modelling packet loss in RTP-based streaming video for residential users

Ellis

Pezaros

Kypraios

et al. 2012

37th Annual IEEE Conference on Local Computer Networks

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Abstract-Packet loss is a major problem for real-time Internet applications. Markov models of packet loss are often used to develop and evaluate the performance of these applications. Despite their wide use, these models have not been validated in terms of how well they capture the loss conditions experienced by residential Internet users. We evaluate the accuracy of common packet loss models using traces of IPTV-like traffic measured on residential ADSL and Cable links, and find that these models are insufficient to capture the observed packet loss patterns. We introduce a new type of model, incorporating packet delay information, and show improved accuracy over previous models.

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On-the-Fly Erasure Coding for Real-Time Video Applications

Cited by 43 publications

References 32 publications

Adaptive Prioritized Random Linear Coding and Scheduling for Layered Data Delivery From Multiple Servers

Adaptive Prioritized Random Linear Coding and Scheduling for Layered Data Delivery From Multiple Servers

PET Protection Optimization for Streaming Scalable Videos With Multiple Transmissions

Modelling packet loss in RTP-based streaming video for residential users

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