Optimal Peer-to-Peer Technique for Massive Content Distribution

Zheng, Xiayu; Cho, C.; Xia, Yibin

doi:10.1109/infocom.2007.39

Cited by 13 publications

(27 citation statements)

References 18 publications

(28 reference statements)

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“…The idea is to use the L multicast trees simultaneously with the correct tree rates. In the modified algorithm, every source computes the time average of the virtual source rates (for releasing virtual packets to the network) that each of its L trees sees; this yields the time averages of the virtual tree rates and these time-average rates converge to the optimal tree rates regardless of the buffer size 7 .…”

Section: Conclusion and Discussionmentioning

confidence: 99%

“…This way, the real rates will not overshoot too much. Note that the adaptation of the real rates and the computation of the time averages are done concurrently; there is no 7 Here, the optimal rate-allocation problem is a modified one. Compared with the original optimization problem, the only modification is that it assumes L fixed trees per multicast session.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

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Algorithms and Stability Analysis for Content Distribution over Multiple Multicast Trees

Zheng

Cho

Xia

2015

IEEE Trans. Parallel Distrib. Syst.

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The paper investigates theoretical issues in applying the universal swarming technique to efficient content distribution. In a swarming session, a file is distributed to all the receivers by having all the nodes in the session exchange file chunks. By universal swarming, not only all the nodes in the session, but also some nodes outside the session may participate in the chunk exchange to improve the distribution performance. We present a universal swarming model where the chunks are distributed along different Steiner trees rooted at the source and covering all the receivers. We assume chunks arrive dynamically at the sources and focus on finding stable universal swarming algorithms. To achieve the throughput region, universal swarming usually involves a tree-selection subproblem of finding a min-cost Steiner tree, which is NP-hard. We propose a universal swarming scheme that employs an approximate treeselection algorithm. We show that it achieves network stability for a reduced throughput region, where the reduction ratio is no more than the approximation ratio of the tree-selection algorithm. We propose a second universal swarming scheme that employs a randomized tree-selection algorithm. It achieves the throughput region, but with a weaker stability result. The proposed schemes and their variants are expected to be useful for infrastructure-based content distribution networks with massive content and relatively stable network environment.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Section: Conclusion and Discussionmentioning

confidence: 99%

Algorithms and Stability Analysis for Content Distribution over Multiple Multicast Trees

Zheng

Cho

Xia

2015

IEEE Trans. Parallel Distrib. Syst.

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“…Along this line, several solutions based on a tree have been proposed in the literature [4,7,8,21]. Some of them define a multicast tree that aims at optimizing the bandwidth use [4,7,22]. Others also deal with scalability by limiting the knowledge each process has about the system [8,21]; yet other systems aim at increasing robustness with respect to packet loss [23][24][25].…”

Section: Related Workmentioning

confidence: 99%

Resource-Aware Multimedia Content Delivery: A Gambling Approach

Allani¹,

Garbinato²,

Pedone³

2009

The Computer Journal

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In this paper, we propose a resource-aware solution to achieving reliable and scalable stream diffusion in a probabilistic model, i.e. where communication links and processes are subject to message losses and crashes, respectively. Our solution is resource-aware in the sense that it limits the memory consumption, by strictly scoping the knowledge each process has about the system, and the bandwidth available to each process, by assigning a fixed quota of messages to each process. We describe our approach as gambling in the sense that it consists in accepting to give up on a few processes sometimes, in the hope of better serving all processes most of the time. That is, our solution deliberately takes the risk not to reach some processes in some executions, in order to reach every process in most executions. The underlying stream diffusion algorithm is based on a tree-construction technique that dynamically distributes the load of forwarding stream packets among processes, based on their respective available bandwidths. Simulations show that this approach pays off when compared to traditional gossiping, when the latter faces identical bandwidth constraints.

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“…A similar problem was addressed in [7] in the context of separate swarming. The rate-allocation problem in universal swarming is substantially more difficult.…”

Section: Introductionmentioning

confidence: 99%

Content distribution by multiple multicast trees and intersession cooperation: Optimal algorithms and approximations

Zheng

Cho

Xia

2009

Proceedings of the 48h IEEE Conference on Decision and Control (CDC) Held Jointly With 2009 28th Chinese Control Conference

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Abstract-The paper addresses the problem of massive content distribution in the network where multiple sessions coexist. In the traditional approaches, the sessions form separate overlay networks and operate independently from each other. In this case, some sessions may suffer from insufficient resources (e.g., aggregate upload bandwidth) even though other sessions have excessive resources. To cope with this problem, we consider the universal swarming approach, which allows multiple sessions cooperate with each other by forming a shared overlay network. We formulate the problem of finding the optimal resource allocation to maximize the sum of the session utilities under the network capacity constraints. The solution turns out to be optimal sharing of multiple minimum-cost multicast trees. We first present a subgradient algorithm and prove that, although the algorithm uses a single multicast tree per session at each iteration and hence does not converge in the conventional sense, it converges to the optimal solution in the time-average sense. The solution involves an NP-hard subproblem of finding a minimumcost Steiner tree. We cope with this difficulty by using a column generation method, which reduces the number of Steiner-tree computation. Furthermore, we allow the use of approximate solutions to the Steiner-tree subproblem. We show that the approximation ratio to the overall problem turns out to be the same as that to the Steiner-tree subproblem. We give some experimental results showing that universal swarming improves the performance of resource-poor sessions with negligible impact to resource-rich sessions.

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Optimal Peer-to-Peer Technique for Massive Content Distribution

Cited by 13 publications

References 18 publications

Algorithms and Stability Analysis for Content Distribution over Multiple Multicast Trees

Algorithms and Stability Analysis for Content Distribution over Multiple Multicast Trees

Resource-Aware Multimedia Content Delivery: A Gambling Approach

Content distribution by multiple multicast trees and intersession cooperation: Optimal algorithms and approximations

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