P2P Streaming Capacity under Node Degree Bound

Shao, Lei; Chen, Minghua; Sengupta, Sudipta; Chiang, Mung; Li, Jin; Chou, Phil

doi:10.1109/icdcs.2010.39

Cited by 56 publications

(54 citation statements)

References 21 publications

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“…A standard approach in structured streaming involved multicast trees, and often with constant-degree nodes [23]- [25]. Several approaches have been presented towards the management of the trees.…”

Section: Related Workmentioning

confidence: 99%

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Deterministic Near-Optimal P2P Streaming

Venkatakrishnan

Viswanath

2015

SIGMETRICS Perform. Eval. Rev.

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We consider streaming over a peer-to-peer network with homogeneous nodes in which a single source broadcasts a data stream to all the users in the system. Peers are allowed to enter or leave the system (adversarially) arbitrarily. Previous approaches for streaming in this setting have either used randomized distribution graphs or structured trees with randomized maintenance algorithms. Randomized graphs handle peer churn well but have poor connectivity guarantees, while structured trees have good connectivity but have proven hard to maintain under peer churn. We improve upon both approaches by presenting a novel distribution structure with a deterministic and distributed algorithm for maintenance under peer churn; our result is inspired by a recent work [1] proposing deterministic algorithms for rumor spreading in graphs.A key innovation in our approach is in having redundant links in the distribution structure. While this leads to a reduction in the maximum streaming rate possible, we show that for the amount of redundancy used, the delay guarantee of the proposed algorithm is near optimal. We introduce a tolerance parameter that captures the worst-case transient streaming rate received by the peers during churn events and characterize the fundamental tradeoff between rate, delay and tolerance. A natural generalization of the deterministic algorithm achieves this tradeoff near optimally. Finally, the proposed deterministic algorithm is robust enough to handle various generalizations: ability to deal with heterogeneous node capacities of the peers and more complicated streaming patterns where multiple source transmissions are present.

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Section: Related Workmentioning

confidence: 99%

“…While trees offer good playback rate and delay, managing trees in a distributed fashion can be very difficult under peer churn. It is known that the complexity of maintaining trees grows with the number of nodes [8], [9]. Hence, random sampling by the peers has commonly been used to help maintain the distribution trees [10].…”

Section: Introductionmentioning

confidence: 99%

Deterministic Near-Optimal P2P Streaming

Venkatakrishnan

Viswanath

2015

SIGMETRICS Perform. Eval. Rev.

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“…Streaming capacity in P2P live systems has been observed in the recent literature [4][5][6][7]. Most recent work was done to improve the efficiency and performance of P2P streaming systems.…”

Section: Related Workmentioning

confidence: 99%

“…Liu et al investigated the performance bounds for minimum server load, maximum streaming rate, and minimum tree depth in tree-based P2P live systems [6]. The streaming capacity under node degree bound is inspected in [7].…”

Section: Related Workmentioning

confidence: 99%

Improving Streaming Capacity in P2P Live Streaming Systems via Resource Sharing

Khan²

2013

IOTCC

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Peer-to-Peer (P2P) streaming systems provide a large number of channels to users. The streaming capacity for a channel is defined as the maximum streaming rate that can be received by every user in the channel. In the this paper, we study the streaming capacity problem in both tree-based and mesh-based P2P live streaming systems. In tree-based multi-channel P2P live streaming systems, we propose a cross-channel resource sharing approach to improve the streaming capacity. We employ cross-channel helpers to establish the cross-channel overlay links, with which the unused upload bandwidths in a channel can be utilized to help the bandwidth-deficient peers in another channel, thus improving the streaming capacity. In meshed-based P2P live streaming systems, we formulate the streaming capacity problem into a resource optimization problem. By solving the resource optimization problem, we can optimally allocate the link rates for each peer to improve the streaming capacity. Through simulations, we demonstrate that the proposed resource sharing approaches can significantly improve the streaming capacity compared to the scheme without resource sharing.

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“…This paper is about the deployment, experiment, measurement, and data analysis over an operational system satisfying all of the above needs. The deployed FastMesh-SIM is a novel pushbased P2P streaming system that consists of multiple trees-as suggested by recent theoretical studies on P2P streaming capacity [3], [5], [6]-to offer high-quality streaming at a global scale, in contrast to other studies that primarily focus on pullbased systems. The two recurring themes of this paper are: 1) engineer 1-Mbps peer-assisted streaming and 2) learn from finegrain measurement through controlled experiments.…”

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confidence: 99%

Global 1-Mbps Peer-Assisted Streaming: Fine-Grain Measurement of a Configurable Platform

Jiang

Chan

Chiang

et al. 2012

IEEE Trans. Multimedia

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Abstract-High-resolution video is defining a new age of peer-assisted video streaming over the public Internet. Streaming over 1-Mbps videos in a scalable and global manner presents a challenging milestone. In this work, we examine the feasibility of 1-Mbps streaming through a global measurement study. In contrast to previous measurement studies that crawl commercial applications, we conduct fine-grain, controlled experiments on a configurable platform. We developed and deployed FastMesh-SIM, a novel peer-assisted streaming system that leverages proxies, scalable streaming trees and IP multicast to achieve 1-Mbps streaming at a global scale.With the configurability-enabled design, we are allowed to conduct controlled experiments by varying design decisions under a wide range of operating conditions, and measuring in-depth, finegrain metrics at a per-hop, per-segment level. We collected hundreds of hours of streaming traces that broadcast live TV channels to more than 120 peers and 30 proxies, with a global geographic footprint over 8 different countries. Data analysis demonstrates how a set of design decisions collectively overcome the 1-Mbps barrier. The various operational issues we uncovered provide insights to service providers that want to deploy a commercial system at a larger scale and a higher streaming rate. By comparing theory and practice, we also confirm theory-inspired architectural decisions, and show that our system indeed achieves throughputs close to theoretical upper-bound calculated under many ideal assumptions.

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P2P Streaming Capacity under Node Degree Bound

Cited by 56 publications

References 21 publications

Deterministic Near-Optimal P2P Streaming

Deterministic Near-Optimal P2P Streaming

Improving Streaming Capacity in P2P Live Streaming Systems via Resource Sharing

Global 1-Mbps Peer-Assisted Streaming: Fine-Grain Measurement of a Configurable Platform

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