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Efficient distributed computation of distance sketches in networks

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Abstract

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.

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Notes

  1. We simply use the terminology “sketch” throughout this paper, if only for the sake of brevity).

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Authors and Affiliations

  1. eBay Research Labs, San Jose, CA, USA

    Atish Das Sarma

  2. Johns Hopkins University, Baltimore, MD, USA

    Michael Dinitz

  3. Department of Computer Science, University of Houston, Houston, TX, 77204, USA

    Gopal Pandurangan

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  1. Atish Das Sarma
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  2. Michael Dinitz
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  3. Gopal Pandurangan
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Correspondence to Gopal Pandurangan.

Additional information

A preliminary version of this paper appeared in the proceedings of the 24th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), Pittsburgh, PA, USA, 2012.

Michael Dinitz: Work supported in part by an Israel Science Foundation Grant #452/08, a US-Israel BSF Grant #2010418, and by a Minerva grant.

Gopal Pandurangan: Work done when the author was at the Division of Mathematical Sciences, Nanyang Technological University, Singapore 637371, and Department of Computer Science, Brown University, Providence, RI, 02912, USA. Research supported in part by the following grants: Nanyang Technological University Grant M58110000, Singapore Ministry of Education (MOE) Academic Research Fund (AcRF) Tier 2 Grant MOE2010-T2-2-082, and the United States-Israel Binational Science Foundation Grant 2008348.

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Sarma, A.D., Dinitz, M. & Pandurangan, G. Efficient distributed computation of distance sketches in networks. Distrib. Comput. 28, 309–320 (2015). https://doi.org/10.1007/s00446-015-0246-7

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