Contribution-based peer selection for packet protection for P2P video streaming over mesh-based networks
29 Dec 2011-pp 2233-2236
TL;DR: Simulation results demonstrate that the proposed distributed packet protection mechanism can effectively mitigate packet loss in a mesh-based P2P network.
Abstract: This paper proposes a distributed packet protection mechanism that can minimize the packet loss probability for mesh based P2P video streaming systems. The proposed scheme combines a peer selection method with forward error correction (FEC) codes. The parent peers select the child peers, which can achieve the minimal packet loss probability compared to other candidate child peers, to transmit the FEC redundant substream. Moreover, the proposed scheme utilizes a packet loss model to estimate the packet loss probability in a mesh based P2P network. The packet loss propagation among peers is modeled through Markov random field (MRF). Simulation results demonstrate that our scheme can effectively mitigate packet loss in a mesh-based P2P network.
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TL;DR: Simulation results demonstrate that the sender-driven peer selection scheme significantly mitigates packet loss in a mesh-based P2P network, compared to other state-of-the-art schemes.
Abstract: This paper proposes a sender-driven peer selection scheme, including estimation of packet loss propagation, evaluation of peers' contributions, and peer selection based on child-peers' contributions, for mesh-based peer-to-peer (P2P) video streaming systems. The proposed packet loss propagation model takes into account the link packet drop rate, peer dynamics, and forward error correction protection to capture the heterogeneous packet loss behavior of individual substreams transmitted over a mesh network. The evaluation of candidate peers' contributions is modeled through Markov random fields to significantly reduce complexity. Simulation results demonstrate that our peer selection scheme significantly mitigates packet loss in a mesh-based P2P network, compared to other state-of-the-art schemes.
11 citations
TL;DR: A survey on users’ experiences with live video in selected locations in Nigeria revealed a 7.4% and 28% reduction in start-up and in end-to-end delays and 9% increase in throughput, respectively, in the proposed adaptive P2P streaming protocol.
Abstract: The recent global demand for video streaming applications has paved the way for peer-to-peer streaming system (P2PSS). Strategic scheduling scheme and dynamic overlay topology are essential to maintain quality of service (QoS) and quality of experience (QoE) in P2PSS. The concept of P2PSS was tailored towards relying on active peers’ bandwidth to achieve cheap and scalable means of distribution over the Internet, such that peers with highest bandwidth serve as backbones for others. However, selecting backbone peers in low-capacity network environment is challenging due to insufficient bandwidth and poor infrastructure, thereby resulting in poor QoS and unpleasant user’s QoE. In this paper, we conducted a survey on users’ experiences with live video in selected locations in Nigeria. We designed an adaptive P2P streaming protocol and performed a packet-level simulation in Network Simulator 3(NS-3). Diverse simulation scenarios were set up to evaluate the proposed streaming protocol. Trace files data were analysed to measure end-to-end delay, start-up delay, and throughput. Furthermore, the proposed streaming protocol was benchmarked against selected existing schemes. The evaluation results revealed a 7.4% and 28% reduction in start-up and in end-to-end delays and 9% increase in throughput.
3 citations
01 Sep 2013
TL;DR: Simulation results demonstrate that the proposed hybrid sender/receiver-driven error protection scheme to transmit scalable video packets over packet-lossy peer-to-peer networks significantly improves visual quality, compared to other state-of-the-art schemes.
Abstract: This paper proposes a hybrid sender/receiver-driven error protection scheme to transmit scalable video packets over packet-lossy peer-to-peer networks. In our scheme, given an estimated system uplink capacity, a joint source-channel coding (JSCC) mechanism based on receiver-driven subscriptions is proposed to minimize the visual distortion received by child-peers by subscribing to appropriate amounts of source and channel coding packets. Because the bandwidth for inter-peer transmissions may fluctuate largely due to peer dynamics, in our method peers estimate the available system uplink capacity based on consensus propagation to avoid the fluctuating allocations of JSCC. To efficiently utilize the uplink bandwidth of peers, parent-peers use sender-driven contribution-guided peer selection to reject the low-contribution subscriptions requested from candidate child-peers. Simulation results demonstrate that our method significantly improves visual quality, compared to other state-of-the-art schemes.
1 citations
Cites methods from "Contribution-based peer selection f..."
...Index Terms—peer-to-peer video streaming, scalable video coding (SVC), forward error correction, joint source-channel coding....
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References
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Book•
01 Aug 1995TL;DR: This book presents a comprehensive study on the use of MRFs for solving computer vision problems, and covers the following parts essential to the subject: introduction to fundamental theories, formulations of MRF vision models, MRF parameter estimation, and optimization algorithms.
Abstract: From the Publisher:
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms systematically when used with optimization principles. This book presents a comprehensive study on the use of MRFs for solving computer vision problems. The book covers the following parts essential to the subject: introduction to fundamental theories, formulations of MRF vision models, MRF parameter estimation, and optimization algorithms. Various vision models are presented in a unified framework, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation. This book is an excellent reference for researchers working in computer vision, image processing, statistical pattern recognition, and applications of MRFs. It is also suitable as a text for advanced courses in these areas.
1,333 citations
01 Jan 2011
676 citations
TL;DR: This paper uses a set of real traces and attempts to develop some theoretical basis to demonstrate that a random peer partnership selection with a hybrid pull-push scheme has the potentially to scale.
Abstract: Peer-to-peer (P2P) technology has found much success in applications like file distributions and VoIP yet, its adoption in live video streaming remains as an elusive goal. Our recent success in Coolstreaming system brings promises in this direction; however, it also reveals that there exist many practical engineering problems in real live streaming systems over the Internet. Our focus in this paper is on a nonoptimal real working system, in which we illustrate a set of existing practical problems and how they could be handled. We believe this is essential in providing the basic understanding of P2P streaming systems. This paper uses a set of real traces and attempts to develop some theoretical basis to demonstrate that a random peer partnership selection with a hybrid pull-push scheme has the potentially to scale. Specifically, first, we describe the fundamental system design tradeoffs and key changes in the design of a Coolstreaming system including substreaming, buffer management, scheduling and the adopt of a hybrid pull-push mechanism over the original pull-based content delivery approach; second, we examine the overlay topology and its convergence; third, using a combination of real traces and analysis, we quantitatively provide the insights on how the buffering technique resolves the problems associated with dynamics and heterogeneity; fourth, we show how substream and path diversity can help to alleviate the impact from congestion and churns; fifth, we discuss the system scalability and limitations.
213 citations
"Contribution-based peer selection f..." refers background in this paper
...The receiver can fully reconstruct the original signal if at least any k out of n packets are received....
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29 Dec 2011
TL;DR: It is shown that the approximation can be largely improved by tuning the PSF samples and interpolation weights with respect to a given continuous model, and regularized reconstruction with the developed blurring model leads to large improvements over existing results.
Abstract: Image deblurring is essential to high resolution imaging and is therefore widely used in astronomy, microscopy or computational photography. While shift-invariant blur is modeled by convolution and leads to fast FFT-based algorithms, shift-variant blurring requires models both accurate and fast. When the point spread function (PSF) varies smoothly across the field, these two opposite objectives can be reached by interpolating from a grid of PSF samples. Several models for smoothly varying PSF co-exist in the literature. We advocate that one of them is both physically-grounded and fast. Moreover, we show that the approximation can be largely improved by tuning the PSF samples and interpolation weights with respect to a given continuous model. This improvement comes without increasing the computational cost of the blurring operator. We illustrate the developed blurring model on a deconvo-lution application in astronomy. Regularized reconstruction with our model leads to large improvements over existing results.
45 citations
29 Dec 2011
TL;DR: Modified-CS-residual provides a fast, yet accurate, reconstruction approach that is able to accurately track the changes of the active pixels, while using only about 30% measurements per frame.
Abstract: In this work, we study the application of compressive sensing (CS) based approaches for blood oxygenation level dependent (BOLD) contrast functional MR imaging (fMRI). In particular, we show, via exhaustive experiments on actual MR scanner data for brain fMRI, that our recently proposed approach for recursive reconstruction of sparse signal sequences, modified-CS-residual, outperforms other existing CS based approaches. Modified-CS-residual exploits the fact that the sparsity pattern of brain fMRI sequences and their signal values change slowly over time. It provides a fast, yet accurate, reconstruction approach that is able to accurately track the changes of the active pixels, while using only about 30% measurements per frame. Significantly improved performance over existing work is shown in terms of practically relevant metrics such as active pixel time courses, activation maps and receiver operating characteristic (ROC) curves.
31 citations