Rate-optimal schemes for Peer-to-Peer live streaming

Massoulié, Laurent; Twigg, Andrew

doi:10.1016/j.peva.2008.03.003

Cited by 22 publications

(21 citation statements)

References 7 publications

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“…The notion of connecting to users that can provide a content flow of interest is similar to peer-to-peer live streaming systems [20]. Unlike peerto-peer streaming, we do not aim to satisfy flow rates, rather our aim is to connect to as many sets of relevant flows as possible.…”

Section: Related Workmentioning

confidence: 99%

Self-organizing flows in social networks

Hegde¹,

Massoulié

Viennot

2015

Theoretical Computer Science

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Social networks offer users new means of accessing information, essentially relying on "social filtering", i.e. propagation and filtering of information by social contacts. The sheer amount of data flowing in these networks, combined with the limited budget of attention of each user, makes it difficult to ensure that social filtering brings relevant content to interested users. Our motivation in this paper is to measure to what extent self-organization of a social network results in efficient social filtering.To this end we introduce flow games, a simple abstraction that models network formation under selfish dynamics, featuring user-specific * Part of this work was done while at Technicolor. † Supported by the Inria project-team "Gang" in the "LIAFA" laboratory and by the "LINCS" laboratory. 1interests and budget of attention. In the context of homogeneous user interests, we show that selfish dynamics converge to a stable network structure (namely a pure Nash equilibrium) with close-to-optimal information dissemination. We show that, in contrast, for the more realistic case of heterogeneous interests, selfish dynamics may lead to information dissemination that can be arbitrarily inefficient, as captured by an unbounded "price of anarchy".Nevertheless the situation differs when user interests exhibit a particular structure, captured by a metric space with low doubling dimension. In that case, natural autonomous dynamics converge to a stable configuration. Moreover, users obtain all the information of interest to them in the corresponding dissemination, provided their budget of attention is logarithmic in the size of their interest set.

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Section: Related Workmentioning

confidence: 99%

Self-organizing flows in social networks

Hegde¹,

Massoulié

Viennot

2015

Theoretical Computer Science

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“…Similarly to [7] it can be shown that the processes (ĉ N , Y N ) N converge in probability for the topology of uniform convergence on finite intervals to the set of fluid trajectories S(c, y) as N → ∞.…”

Section: A Fluid Limitsmentioning

confidence: 90%

“…In [7] the authors prove that Random Useful (RU) is rate-optimal for a fixed rate allocation c 0 . That is, when using RU if the value of the min-min-cut of the edgecapacitated graph (G, c 0 ) with source node s is greater than λ, then rate λ is attained at each receiver.…”

Section: A First Approachmentioning

confidence: 99%

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Flow Control for Cost-Efficient Peer-to-Peer Streaming

Tomozei

Massoulié

2010

2010 Proceedings IEEE INFOCOM

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Abstract-In this paper we address the issue of network cost efficiency for live streaming peer-to-peer systems. We formalize this as an optimization problem, which features a generic cost function. The latter is appropriate to capture not only ISPspecific link weights, but also non-linear, congestion-dependent costs. Our main contribution is the introduction of the ImplicitPrimal-Dual scheme for flow control in live streaming peer-topeer systems. It is fully distributed in that it relies only on local state variable exchanges. Moreover, we show that at a fluid scale, combined with random linear network coding, it admits the cost optimal operating point as a fixed point. We also prove asymptotic boundedness of fluid trajectories for particular cost functions. We finally show via experiments that these optimality properties are resilient to operational constraints such as finite generation size and finite field size.

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“…Por exemplo, modelos para determinar o impacto dos mecanismos de incentivo e das taxas de upload e download sobre a performance; do efeito do chamado free riding [2]; da forma com que arquivos são disseminados; e modelos para estudar a equidade (fairness) do sistema e ainda a disponibilidade de conteúdo no swarm [3], [4]. Além disso, estudos têm sido realizados sobre as estratégias de distribuição de blocos (pieces) e escolha dos peers para transmissão [5].…”

Section: Introductionunclassified

On the Service Capacity of P2P Systems

Silva

Leão

Menasché

et al. 2014

2014 Brazilian Symposium on Computer Networks and Distributed Systems

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One of the most fundamental problems in the realm of peer-to-peer systems consists of determining their service capacity. In this paper, we first propose a new Markovian model to compute the throughput of peer-to-peer systems. Then, we present a simple approximate model for obtaining the system throughput for large peer populations. From the models, we obtain novel insights on the behavior of P2P swarming systems which motivate new mechanisms for publishers and peers to improve the overall performance. In particular, we show that if publishers adopt the most deprived peer selection, and peers reduce their service rate when they have all the file blocks but one, the system's capacity can significantly increase.Index Terms-scalability, peer-to-peer systems, analytical model, P2P I. INTRODUÇÃOSistemas par-a-par (peer-to-peer ou P2P) têm tido muito sucesso na disseminação de conteúdo na Internet e importantes empresas têm adotado essa arquitetura. Por exemplo, a Blizzard entertainment distribui arquivos grandes via o Blizzard downloader queé baseado no BitTorrent Opensource. O Linux Ubuntu tambémé disponível para download via BitTorrent. A Amazon Simple Storage Service (Amazon S3) e uma infraestrutura de armazenamento e distribuição de dados e também suporta o protocolo BitTorrent para distribuir arquivos. Propostas recentes sugerem o uso de P2P para distribuição de grandes arquivos em redes orientadas a conteúdo [1], dando origem a uma Network Swarm Architecture. Arquiteturas P2P têm sido estudadas por mais de uma década e inúmeros modelos para entender o seu desempenho foram propostos. Por exemplo, modelos para determinar o impacto dos mecanismos de incentivo e das taxas de upload e download sobre a performance; do efeito do chamado free riding [2]; da forma com que arquivos são disseminados; e modelos para estudar a equidade (fairness) do sistema e ainda a disponibilidade de conteúdo no swarm [3], [4]. Além disso, estudos têm sido realizados sobre as estratégias de distribuição de blocos (pieces) e escolha dos peers para transmissão [5]. Apesar dos inúmeros artigos naárea, apenas recentemente a escalabilidade do sistema começou a ser melhor equacionada. Em outras palavras, sistemas P2P eram ditos escaláveis uma vez que cada novo usuário no sistema a ele acrescenta novos recursos e, portanto, a capacidade total disponível deveria aumentar proporcionalmente aos recursos incorporados. Consequentemente,é esperado que a vazão do sistema cresça linearmente e sem limites com o aumento da população. Entretanto, limitações intrínsecasà arquitetura P2P têm sido observadas. Recentemente Hajek e Zhou [6] mostraram que se a taxa de chegada λ de peers no sistema for maior que a capacidade U do servidor de conteúdo dedicada ao swarm, a população de usuários cresce sem limites quando peers e blocos são escolhidos de forma aleatória. Menasché et al [7] avaliaram o impacto de diferentes estratégias e parâmetros do sistema sobre a sua vazão (ou, analogamente, sobre a estabilidade do sistema). Os resultados indicaram que, quando o se...

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Rate-optimal schemes for Peer-to-Peer live streaming

Cited by 22 publications

References 7 publications

Self-organizing flows in social networks

Self-organizing flows in social networks

Flow Control for Cost-Efficient Peer-to-Peer Streaming

On the Service Capacity of P2P Systems

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