Given a large edge-weighted network @math with @math terminal vertices, we wish to compress it and store, using little memory, the value of the minimum cut (or equivalently, maximum flow) between every bipartition of terminals. One appealing methodology to implement a compression of @math is to construct a : a small network @math with the same @math terminals, in which the minimum cut value between every bipartition of terminals is the same as in @math . This notion was introduced by Hagerup, Katajainen, Nishimura, and Ragde [JCSS '98], who proved that such @math of size at most @math always exists. Obviously, by having access to the smaller network @math , certain computations involving cuts can be carried out much more efficiently. We provide several new bounds, which together narrow the previously known gap from doubly-exponential to only singly-exponential, both for planar and for general graphs. Our first and main result is that every @math -terminal planar network admits a mimicking network @math of size @math , which is moreover a minor of @math . On the other hand, some planar networks @math require @math . For general networks, we show that certain bipartite graphs only admit mimicking networks of size @math , and moreover, every data structure that stores the minimum cut value between all bipartitions of the terminals must use @math machine words.
Graph compression can be interpreted quite broadly, and indeed it was studied extensively in the past, with many results known for different graphical features (the properties we wish to preserve). For instance, in the context of preserving the graph distances, concepts such as spanners @cite_0 and probabilistic embedding into trees @cite_10 @cite_1 , have developed into a rich area with productive area, and variations of it that involve a subset of terminal vertices were studied more recently, see e.g. @cite_9 @cite_13 .
@cite_13 @cite_9 @cite_1 @cite_0 @cite_10
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We introduce the following notion of compressing an undirected graph G with (nonnegative) edge-lengths and terminal vertices R⊆V(G). A distance-preserving minor is a minor G′ (of G) with possibly different edge-lengths, such that R⊆V(G′) and the shortest-path distance between every pair of terminals is exactly the same in G and in G′. We ask: what is the smallest f*(k) such that every graph G with k=|R| terminals admits a distance-preserving minor G′ with at most f*(k) vertices? Simple analysis shows that f*(k)≤O(k4). Our main result proves that f*(k)≥Ω(k2), significantly improving over the trivial f*(k)≥k. Our lower bound holds even for planar graphs G, in contrast to graphs G of constant treewidth, for which we prove that O(k) vertices suffice. We introduce and study the notions of pairwise and sourcewise preservers. Given an undirected N-vertex graph G = (V,E) and a set P of pairs of vertices, let G' = (V,H), H E, be called a pairwise preserver of G with respect to P if for every pair u,w P, distG'(u,w) = distG(u,w). For a set S V of sources, a pairwise preserver of G with respect to the set of all pairs P = (S 2) of sources is called a sourcewise preserver of G with respect to S. We prove that for every undirected possibly weighted N-vertex graph G and every set P of P = O(N1 2) pairs of vertices of G, there exists a linear-size pairwise preserver of G with respect to P. Consequently, for every subset S V of S = O(N1 4) sources, there exists a linear-size sourcewise preserver of G with respect to S. On the negative side we show that neither of the two exponents (1 2 and 1 4) can be improved even when the attention is restricted to unweighted graphs. Our lower bounds involve constructions of dense convexly independent sets of vectors with small Euclidean norms. We believe that the link between the areas of discrete geometry and spanners that we establish is of independent interest and might be useful in the study of other problems in the area of low-distortion embeddings. This paper provides a novel technique for the analysis of randomized algorithms for optimization problems on metric spaces, by relating the randomized performance ratio for any, metric space to the randomized performance ratio for a set of "simple" metric spaces. We define a notion of a set of metric spaces that probabilistically-approximates another metric space. We prove that any metric space can be probabilistically-approximated by hierarchically well-separated trees (HST) with a polylogarithmic distortion. These metric spaces are "simple" as being: (1) tree metrics; (2) natural for applying a divide-and-conquer algorithmic approach. The technique presented is of particular interest in the context of on-line computation. A large number of on-line algorithmic problems, including metrical task systems, server problems, distributed paging, and dynamic storage rearrangement are defined in terms of some metric space. Typically for these problems, there are linear lower bounds on the competitive ratio of deterministic algorithms. Although randomization against an oblivious adversary has the potential of overcoming these high ratios, very little progress has been made in the analysis. We demonstrate the use of our technique by obtaining substantially improved results for two different on-line problems. This paper investigates a zero-sum game played on a weighted connected graph @math between two players, the tree player and the edge player. At each play, the tree player chooses a spanning tree @math and the edge player chooses an edge @math . The payoff to the edge player is @math , defined as follows: If @math lies in the tree @math then @math ; if @math does not lie in the tree then @math , where @math is the weight of edge @math and @math is the weight of the unique cycle formed when edge @math is added to the tree @math . The main result is that the value of the game on any @math -vertex graph is bounded above by @math . It is conjectured that the value of the game is @math . The game arises in connection with the @math -server problem on a road network; i.e., a metric space that can be represented as a multigraph @math in which each edge @math represents a road of length @math . It is shown that, if the value of the game on @math is @math , then there is a randomized strategy that achieves a competitive ratio of @math against any oblivious adversary. Thus, on any @math -vertex road network, there is a randomized algorithm for the @math -server problem that is @math competitive against oblivious adversaries. At the heart of the analysis of the game is an algorithm that provides an approximate solution for the simple network design problem. Specifically, for any @math -vertex weighted, connected multigraph, the algorithm constructs a spanning tree @math such that the average, over all edges @math , of @math is less than or equal to @math . This result has potential application to the design of communication networks. It also improves substantially known estimates concerning the existence of a sparse basis for the cycle space of a graph.