This paper presents efficient deterministic and ran-domized distributed algorithms for decomposing a graph with n nodes into a disjoint set of connected clusters with small radius and few intercluster edges. Our al-gorithms can be easily implemented in the distributed CONGEST model of computation i.e., limited message size, improving the time complexity of previous algo-rithms [27, 3, 29] from linear to sublinear. One im-portant application of our algorithms is efficient con-struction of sparse graph spanners. In fact, given a pa-rameter k, we show that there exists a sublinear deter-ministic distributed algorithm that constructs a graph spanner of stretch 2k−1 with at most O(n1+1/k) edges in the CONGEST model
Balanced graph partitioning is an NP-complete problem with a wide range of applications. These appli...
Balanced graph partitioning is anNP-complete problemwith a wide range of applications. These applica...
We develop a novel parallel decomposition strategy for unweighted, undirected graphs, based on grow...
Abstract. We present new efficient deterministic and randomized distributed algorithms for decomposi...
International audienceWe present new efficient deterministic and randomized distributed algorithms f...
Abstract We present new efficient deterministic and randomized distributed algo-rithms for decomposi...
AbstractThis paper concerns the efficient construction of sparse and low stretch spanners for unweig...
The paper presents a deterministic distributed algorithm that, given k> 1, con-structs in k round...
Graph clustering is a fundamental computational problem with a number of applications in algorithm d...
A fundamental problem in distributed network algorithms is to obtain information flow matching the c...
Rapport de rechercheThe paper presents a deterministic distributed algorithm that, given k>0, constr...
Abstract. The most commonly used method to tackle the graph partitioning problem in practice is the ...
This paper presents efficient distributed algorithms for a number of fundamental problems in the are...
Graph spanners are fundamental graph structures with a wide range of applications in distributed net...
Balanced graph partitioning is a well known NP-complete problem with a wide range of applications. T...
Balanced graph partitioning is an NP-complete problem with a wide range of applications. These appli...
Balanced graph partitioning is anNP-complete problemwith a wide range of applications. These applica...
We develop a novel parallel decomposition strategy for unweighted, undirected graphs, based on grow...
Abstract. We present new efficient deterministic and randomized distributed algorithms for decomposi...
International audienceWe present new efficient deterministic and randomized distributed algorithms f...
Abstract We present new efficient deterministic and randomized distributed algo-rithms for decomposi...
AbstractThis paper concerns the efficient construction of sparse and low stretch spanners for unweig...
The paper presents a deterministic distributed algorithm that, given k> 1, con-structs in k round...
Graph clustering is a fundamental computational problem with a number of applications in algorithm d...
A fundamental problem in distributed network algorithms is to obtain information flow matching the c...
Rapport de rechercheThe paper presents a deterministic distributed algorithm that, given k>0, constr...
Abstract. The most commonly used method to tackle the graph partitioning problem in practice is the ...
This paper presents efficient distributed algorithms for a number of fundamental problems in the are...
Graph spanners are fundamental graph structures with a wide range of applications in distributed net...
Balanced graph partitioning is a well known NP-complete problem with a wide range of applications. T...
Balanced graph partitioning is an NP-complete problem with a wide range of applications. These appli...
Balanced graph partitioning is anNP-complete problemwith a wide range of applications. These applica...
We develop a novel parallel decomposition strategy for unweighted, undirected graphs, based on grow...