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Efficient distributed computation of distance sketches in networks

机译:网络中距离草图的高效分布式计算

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Distance computation (e.g., computing shortest paths) is one of the most fundamental primitives used in communication networks. The cost of effectively and accurately computing pairwise network distances can become prohibitive in large-scale networks such as the Internet and Peer-to-Peer (P2P) networks. The idea behind distance sketches is to preprocess the graph and store a small amount of information (called as sketch or distance label) such that whenever a query for any pairwise distance is issued, the distance can be well approximated (i.e., with small stretch) very quickly in an online fashion. Specifically, the pre-processing (usually) involves storing this sketch with each node, such that at query time only the sketches of the concerned nodes need to be looked up to compute the approximate distance. In this paper, we present the first theoretical study of distance sketches derived from distance oracles in a distributed network. We first present a fast distributed algorithm for computing approximate distance sketches, based on a distributed implementation of the distance oracle scheme of (Thorup and Zwick, J ACM 52(1):1-24, 2005). We also show how to modify this basic construction to achieve different tradeoffs between the number of pairs for which the distance estimate is accurate, the size of the sketches, and the time and message complexity necessary to compute them. These tradeoffs can then be combined to give an efficient construction of small sketches with provable average-case as well as worst-case performance. Our algorithms use only small-sized messages and hence are suitable for bandwidth-constrained networks, and can be used in various networking applications such as topology discovery and construction, token management, load balancing, monitoring overlays, and several other problems in distributed algorithms.
机译:距离计算(例如,计算最短路径)是通信网络中使用的最基本的原语之一。在Internet和对等(P2P)网络等大型网络中,有效且准确地计算成对网络距离的成本可能会变得过高。距离草图的想法是对图形进行预处理并存储少量信息(称为草图或距离标签),以便每当发出任何成对距离的查询时,就可以很好地近似该距离(即,拉伸很小)以在线方式非常迅速。具体来说,预处理(通常)涉及将这个草图与每个节点一起存储,从而在查询时仅需要查找有关节点的草图以计算近似距离。在本文中,我们提出了对分布式网络中距离预言的派生距离草图的第一个理论研究。我们首先基于(Thorup and Zwick,J ACM 52(1):1-24,2005)的距离预言系统的分布式实现,提出一种用于计算近似距离草图的快速分布式算法。我们还将展示如何修改此基本构造,以在距离估计准确的线对数量,草图的大小以及计算草图所需的时间和消息复杂度之间取得不同的权衡。然后,可以权衡这些折衷,以有效构造具有可证明的平均用例和最坏用例性能的小草图。我们的算法仅使用小型消息,因此适用于带宽受限的网络,并且可用于各种网络应用程序,例如拓扑发现和构建,令牌管理,负载平衡,监视覆盖以及分布式算法中的其他一些问题。

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