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On the impact of popularity decays in peer-to-peer VoD systems

机译:在点对点VoD系统中流行度下降的影响

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Today's peer-to-peer (P2P) Video-on-Demand (VoD) systems are known to be highly scalable in a steady state. For the dynamic scenario, much effort has been spent on accommodating sharply increasing requests (known as flash crowd) with effective solutions being developed. The high popularity upon a flash crowd however does not necessarily last long, and indeed often drops very fast after the peak. Compared to growth, a decay is seemingly less challenging or even beneficial given the less user demands. While this is true in a conventional client/server system, we find that it is not the case for peer-to-peer. A quick decay can easily de-stabilize an established overlay, and the resultant smaller overlay is generally less effective for content sharing. The replication of data segments, which is critical during flash crowd, will not promptly respond to a fast and globalized population decay, either. Many of the replicas can become redundant and, even worse, their spaces cannot be utilized for an extended period. In this paper, we seek to understand the impact of such decays and the key influential factors. To this end, we develop a mathematical model to trace the evolution of peer upload and replication during population churns, specifically during decays. Our model captures peer behaviors with common data replication and scheduling strategies in state-of-the-art peer-to-peer VoD systems. It quantitatively reveals the root causes toward escalating server load during a population decay. The model also facilitates the design of a flexible server provision to serve highly time-varying demands.
机译:众所周知,当今的点对点(P2P)视频点播(VoD)系统在稳定状态下具有很高的可伸缩性。对于动态方案,已经花了很多精力来适应急剧增长的请求(称为闪存人群),并且正在开发有效的解决方案。然而,在闪光人群中的高人气并不一定持续很长时间,并且实际上经常在高峰之后下降得很快。与增长相比,鉴于用户需求减少,衰减似乎没有那么大的挑战甚至是有益的。尽管在传统的客户端/服务器系统中确实如此,但我们发现对等情况并非如此。快速衰减会轻易破坏已建立的叠加层的稳定性,因此,生成的较小的叠加层通常对内容共享的效果较差。数据段的复制在闪存人群中至关重要,因此也不会立即响应快速且全球化的种群衰减。许多副本可能变得多余,更糟糕的是,它们的空间无法长时间使用。在本文中,我们试图了解这种衰减的影响以及关键的影响因素。为此,我们开发了一个数学模型来追踪人口流失期间(尤其是在衰退期间)同伴上载和复制的演变。我们的模型使用最新的对等VoD系统中的通用数据复制和调度策略来捕获对等行为。它定量地揭示了人口减少期间导致服务器负载逐步增加的根本原因。该模型还促进了灵活服务器配置的设计,从而可以满足高度随时间变化的需求。

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