摘要：In this paper, we study the online Euclidean spanners problem for points in ℝ^d. Given a set S of n points in ℝ^d, a t-spanner on S is a subgraph of the underlying complete graph G = (S,binom(S,2)), that preserves the pairwise Euclidean distances between points in S to within a factor of t, that is the stretch factor. Suppose we are given a sequence of n points (s₁,s₂,…, s_n) in ℝ^d, where point s_i is presented in step i for i = 1,…, n. The objective of an online algorithm is to maintain a geometric t-spanner on S_i = {s₁,…, s_i} for each step i. The algorithm is allowed to add new edges to the spanner when a new point is presented, but cannot remove any edge from the spanner. The performance of an online algorithm is measured by its competitive ratio, which is the supremum, over all sequences of points, of the ratio between the weight of the spanner constructed by the algorithm and the weight of an optimum spanner. Here the weight of a spanner is the sum of all edge weights. First, we establish a lower bound of Ω(ε^{-1}log n / log ε^{-1}) for the competitive ratio of any online (1+ε)-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+ε)-spanner with competitive ratio O(ε^{-1}log n / log ε^{-1}). Next, we design online algorithms for sequences of points in ℝ^d, for any constant d ≥ 2, under the L₂ norm. We show that previously known incremental algorithms achieve a competitive ratio O(ε^{-(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 ε. We describe an online Steiner (1+ε)-spanner algorithm with competitive ratio O(ε^{(1-d)/2} log n). As a counterpart, we show that the dependence on n cannot be eliminated in dimensions d ≥ In particular, we prove that any online spanner algorithm for a sequence of n points in ℝ^d under the L₂ norm has competitive ratio Ω(f(n)), where lim_{n → ∞}f(n) = ∞. Finally, we provide improved lower bounds under the L₁ norm: Ω(ε^{-2}/log ε^{-1}) in the plane and Ω(ε^{-d}) in ℝ^d for d ≥ 3.
