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Mode-Suppression: A Simple and Provably Stable Chunk-Sharing Algorithm for P2P Networks

机译:模式抑制:一种简单且稳定的P2P网络块共享算法

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The ability of a P2P network to scale its throughput up in proportion to the arrival rate of peers has recently been shown to be crucially dependent on the chunk sharing policy employed. Some policies can result in low frequencies of a particular chunk, known as the missing chunk syndrome, which can dramatically reduce throughput and lead to instability of the system. For instance, commonly used policies that nominally “boost” the sharing of infrequent chunks such as the well-known rarest-first algorithm have been shown to be unstable. Recent efforts have largely focused on the careful design of boosting policies to mitigate this issue. We take a complementary viewpoint, and instead consider a policy that simply prevents the sharing of the most frequent chunk(s). Following terminology from statistics wherein the most frequent value in a data set is called the mode, we refer to this policy as mode suppression. We prove the stability of this algorithm using Lyapunov techniques. We also design a distributed version that suppresses the mode via an estimate obtained by sampling three randomly selected peers. We show numerically that both algorithms perform well at minimizing total download times, with distributed mode suppression outperforming all others that we tested against.
机译:最近显示,P2P网络按对等点的到达速率成比例地增加吞吐量的能力主要取决于所采用的组块共享策略。某些策略可能导致特定块的频率降低,这称为丢失块综合症,这可能会大大降低吞吐量并导致系统不稳定。例如,已证明名义上“促进”不频繁块共享的常用策略(例如众所周知的稀有优先算法)是不稳定的。最近的努力主要集中在精心设计促进该问题的政策上。我们采取互补的观点,而是考虑一种仅阻止共享最频繁的块的策略。根据统计中的术语(其中数据集中最频繁的值称为模式),我们将此策略称为模式抑制。我们使用Lyapunov技术证明了该算法的稳定性。我们还设计了一个分布式版本,该版本通过对三个随机选择的对等点进行采样获得的估计值来抑制该模式。我们用数字显示了这两种算法在最小化总下载时间方面表现良好,而分布式模式抑制的性能优于我们测试过的所有其他算法。

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