In this paper, we show that any n point metric space can be embedded into a distribution over dominating tree metrics such that the expected stretch of any edge is O(log n). This improves upon the result of Bartal who gave a bound of O(log n log log n). Moreover, our result is existentially tight; there exist metric spaces where any tree embedding must have distortion#sto n)-distortion. This problem lies at the heart of numerous approximation and online algorithms including ones for group Steiner tree, metric labeling, buy-at-bulk network design and metrical task system. Our result improves the performance guarantees for all of these problems.

Consider the multicommodity flow problem in which the object is to maximize the sum of commodities routed. We prove the following approximate max-flow min-multicut theorem: min multicut O(logk) max flow min multicut; where k is the number of commodities. Our proof is constructive; it enables us to find a multicut within O(log k) of the max flow (and hence also the optimal multicut). In addition, the proof technique provides a unified framework in which one can also analyse the case of flows with specified demands, of Leighton-Rao and Klein et.al., and thereby obtain an improved bound for the latter problem. 1 Introduction Much of flow theory, and the theory of cuts in graphs, is built around a single theorem - the celebrated max-flow min-cut theorem of Ford and Fulkerson [FF], and Elias, Feinstein and Shannon [EFS]. The power of this theorem lies in that it relates two fundamental graph-theoretic entities via the potent mechanism of a min-max relation. The importance of this theor...

Abstract. It is shown that the minimum cut ratio is within a factor of O(log k) of the maximum concurrent flow for k-commodity flow instances with arbitrary capacities and demands. This improves upon the previously best-known bound of O(log 2 k) and is existentially tight, up to a constant factor. An algorithm for finding a cut with ratio within a factor of O(log k) of the maximum concurrent flow, and thus of the optimal min-cut ratio, is presented.

A principle task in parallel and distributed systems is to reduce the communication load in the interconnection network, as this is usually the major bottleneck for the performance of distributed applications. In this paper we introduce a framework for solving on-line problems that aim to minimize the congestion (i.e. the maximum load of a network link) in general topology networks. We apply this

We devise a new embedding technique, which we call measured descent, based on decomposing a metric space locally, at varying speeds, according to the density of some probability measure.

Bartal [4, 5] gave a randomized polynomial time algorithm that given any n point metric G, constructs a tree T such that the expected stretch (distortion) of any edge is at most O(log n log log n). His result has found several applications and in particular has resulted in approximation algorithms for many graph optimization problems. However approximation algorithms based on his

A bisection of a graph with n vertices is a partition of its vertices into two sets, each of size n=2. The bisection cost is the number of edges connecting the two sets.

Most optimization problems on an undirected graph reduce in complexity when restricted to instances on a tree. A recent result [3] for probabilistically approximating graph metrics by trees such that no edge stretches (in an expected sense) by more than a factor of O(log 2 n) has resulted in several approximation algorithms which exploit the ease of solving problems on trees. The tree construction in [3] is inherently randomized and a natural question to ask is whether approximation algorithms which use this construction can be derandomized. We present a general framework for derandomizing approximation algorithms which use the above tree construction as a primitive. Let \Pi be a graph optimization problem which can be expressed as an integer program with 0-1 variables ¯ x(e) for each edge and with an objective function expressible as...

In the 0-extension problem, we are given a weighted graph with some nodes marked as terminals and a semimetric on the set of terminals. Our goal is to assign the rest of the nodes to terminals so as to minimize the sum, over all edges, of the product of the edge’s weight and the distance between the terminals to which its endpoints are assigned. This problem generalizes the multiway cut problem of Dahlhaus, Johnson, Papadimitriou, Seymour, and Yannakakis and is closely related to the metric labeling problem introduced by Kleinberg and Tardos. We present approximation algorithms for 0-Extension. In arbitrary graphs, we present a O(log k)-approximation algorithm, k being the number of terminals. We also give O(1)approximation guarantees for weighted planar graphs. Our results are based on a natural metric relaxation of the problem, previously considered by Karzanov. It is similar in flavor to the linear programming relaxation of Garg, Vazirani, and Yannakakis for the multicut problem and similar to relaxations for other graph partitioning problems. We prove that the integrality ratio of the metric relaxation is at least c √ lg k for a positive c for infinitely many k. Our results improve some of the results of Kleinberg and Tardos and they further our understanding on how to use metric relaxations.

ABSTRACT R"acke recently gave a remarkable proof showing that any undirected multicommodity flow problem can be routed in an oblivious fashion with congestion that is within a factor of O(log 3 n) of the best off-line solution to the problem. He also presented interesting applications of this result to distributed computing. Maggs, Miller, Parekh, Ravi and Wu have shown that such a decomposition also has an application to speeding up iterative solvers of linear systems. R"acke's construction finds a decomposition tree of the underlying graph, along with a method to obliviously route in a hierarchical fashion on the tree. The construction, however, uses exponential-time procedures to build the decomposition. The non-constructive nature of his result was remedied, in part, by Azar, Cohen, Fiat, Kaplan, and R"acke, who gave a polynomial time method for building an oblivious routing strategy. Their construction was not based on finding a hierarchical decomposition, and this precludes its application to iterative methods for solving linear systems. In this paper, we show how to compute a hierarchical decomposition and a corresponding oblivious routing strategy in polynomial time. In addition, our decomposition gives an improved competitive ratio for congestion of O(log 2 n log log n). In an independent result in this conference, Bienkowski, Korzeniowski, and R"acke give a polynomial-time method for constructing a decomposition tree with competitive ratio O(log 4 n). We note that our original submission used essentially the same algorithm, and we appreciate them allowing us to present this improved version.