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Estimation of the Average Search Length of Random Walks in Power-Law Networks

机译:幂律网络中随机游走的平均搜索长度的估计

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摘要

In this paper we introduce a model to study random walks in power-law networks with one-hop replication. Basically, this model gives a set of expressions that captures how the knowledge about the network evolves as the random walk traverses the network: how many nodes have been known, either because they or their neighbors have been visited by the random walk. With this, we obtain an expression that gives a good estimation of the average number of hops needed to find some random peer from any other random peer. We denote this metric the average search length, and we deem it can be very useful to evaluate random walk based resource location solutions in P2P networks.
机译:在本文中,我们引入一个模型来研究具有单跳复制的幂律网络中的随机游动。基本上,该模型提供了一组表达式,这些表达式捕获了有关随机游走遍历网络时有关网络的知识如何演化的信息:已知多少个节点,这是因为随机游走访问了它们或它们的邻居。这样,我们得到一个表达式,可以很好地估计从任何其他随机对等点中找到某个随机对等点所需的平均跳数。我们将这个指标表示为平均搜索长度,并且我们认为它对评估P2P网络中基于随机游走的资源定位解决方案非常有用。

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