Online Euclidean Spanners


Abstract in English

In this paper, we study the online Euclidean spanners problem for points in $mathbb{R}^d$. Suppose we are given a sequence of $n$ points $(s_1,s_2,ldots, s_n)$ in $mathbb{R}^d$, where point $s_i$ is presented in step~$i$ for $i=1,ldots, n$. The objective of an online algorithm is to maintain a geometric $t$-spanner on $S_i={s_1,ldots, s_i}$ for each step~$i$. First, we establish a lower bound of $Omega(varepsilon^{-1}log n / log varepsilon^{-1})$ for the competitive ratio of any online $(1+varepsilon)$-spanner algorithm, for a sequence of $n$ points in 1-dimension. We show that this bound is tight, and there is an online algorithm that can maintain a $(1+varepsilon)$-spanner with competitive ratio $O(varepsilon^{-1}log n / log varepsilon^{-1})$. Next, we design online algorithms for sequences of points in $mathbb{R}^d$, for any constant $dge 2$, under the $L_2$ norm. We show that previously known incremental algorithms achieve a competitive ratio $O(varepsilon^{-(d+1)}log n)$. However, if the algorithm is allowed to use additional points (Steiner points), then it is possible to substantially improve the competitive ratio in terms of $varepsilon$. We describe an online Steiner $(1+varepsilon)$-spanner algorithm with competitive ratio $O(varepsilon^{(1-d)/2} log n)$. As a counterpart, we show that the dependence on $n$ cannot be eliminated in dimensions $d ge 2$. In particular, we prove that any online spanner algorithm for a sequence of $n$ points in $mathbb{R}^d$ under the $L_2$ norm has competitive ratio $Omega(f(n))$, where $lim_{nrightarrow infty}f(n)=infty$. Finally, we provide improved lower bounds under the $L_1$ norm: $Omega(varepsilon^{-2}/log varepsilon^{-1})$ in the plane and $Omega(varepsilon^{-d})$ in $mathbb{R}^d$ for $dgeq 3$.

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