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# Improved Local Computation Algorithms for Constructing Spanners

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## Cite As

Rubi Arviv, Lily Chung, Reut Levi, and Edward Pyne. Improved Local Computation Algorithms for Constructing Spanners. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 275, pp. 42:1-42:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/LIPIcs.APPROX/RANDOM.2023.42

## Abstract

A spanner of a graph is a subgraph that preserves lengths of shortest paths up to a multiplicative distortion. For every k, a spanner with size O(n^{1+1/k}) and stretch (2k+1) can be constructed by a simple centralized greedy algorithm, and this is tight assuming Erdős girth conjecture. In this paper we study the problem of constructing spanners in a local manner, specifically in the Local Computation Model proposed by Rubinfeld et al. (ICS 2011). We provide a randomized Local Computation Agorithm (LCA) for constructing (2r-1)-spanners with Õ(n^{1+1/r}) edges and probe complexity of Õ(n^{1-1/r}) for r ∈ {2,3}, where n denotes the number of vertices in the input graph. Up to polylogarithmic factors, in both cases, the stretch factor is optimal (for the respective number of edges). In addition, our probe complexity for r = 2, i.e., for constructing a 3-spanner, is optimal up to polylogarithmic factors. Our result improves over the probe complexity of Parter et al. (ITCS 2019) that is Õ(n^{1-1/2r}) for r ∈ {2,3}. Both our algorithms and the algorithms of Parter et al. use a combination of neighbor-probes and pair-probes in the above-mentioned LCAs. For general k ≥ 1, we provide an LCA for constructing O(k²)-spanners with Õ(n^{1+1/k}) edges using O(n^{2/3}Δ²) neighbor-probes, improving over the Õ(n^{2/3}Δ⁴) algorithm of Parter et al. By developing a new randomized LCA for graph decomposition, we further improve the probe complexity of the latter task to be O(n^{2/3-(1.5-α)/k}Δ²), for any constant α > 0. This latter LCA may be of independent interest.

## Subject Classification

##### ACM Subject Classification
• Theory of computation → Streaming, sublinear and near linear time algorithms
##### Keywords
• Local Computation Algorithms
• Spanners

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## References

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