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Proximity-Preserving Labeling Schemes and Their Applications

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1665))

Abstract

This paper considers informative labeling schemes for graphs. Specifically, the question introduced is whether it is possible to label the vertices of a graph with short labels in such a way that the distance between any two vertices can be inferred from inspecting their labels. A labeling scheme enjoying this property is termed a proximity-preserving labeling scheme. It is shown that for the class of n-vertex weighted trees with M-bit edge weights, there exists such a proximity-preserving labeling scheme using O(M log n + log2 n) bit labels. For the family of all n-vertex unweighted graphs, a labeling scheme is proposed that using O(log2 n · k · n 1/k) bit labels can provide approximate estimates to the distance, which are accurate up to a factor of √κ. In particular, using O(log3 n) bit labels the scheme can provide estimates accurate up to a factor of √2 log n. (For weighted graphs, one of the log n factors in the label size is replaced by a factor logarithmic in the network’s diameter.) In addition to their theoretical interest, proximity-preserving labeling systems seem to have some relevance in the context of communication networks. We illustrate this by proposing a potential application of our labeling schemes to efficient distributed connection setup in circuit- switched networks.

Supported in part by grants from the Israel Science Foundation and from the Israel Ministry of Science and Art.

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© 1999 Springer-Verlag Berlin Heidelberg

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Peleg, D. (1999). Proximity-Preserving Labeling Schemes and Their Applications. In: Widmayer, P., Neyer, G., Eidenbenz, S. (eds) Graph-Theoretic Concepts in Computer Science. WG 1999. Lecture Notes in Computer Science, vol 1665. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46784-X_5

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  • DOI: https://doi.org/10.1007/3-540-46784-X_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66731-5

  • Online ISBN: 978-3-540-46784-7

  • eBook Packages: Springer Book Archive

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