A new algorithm for graph center computation and graph partitioning according to the distance to the center

TL;DR

This paper introduces a novel parallel algorithm for identifying a graph's center and partitioning nodes by their distance to it, outperforming Floyd-Warshall on various graph types.

Contribution

The paper presents a new parallel algorithm for graph center computation and node ranking, offering improved performance over traditional methods like Floyd-Warshall.

Findings

Outperforms Floyd-Warshall on many graph types

Efficient parallelizable approach

Effective for large graphs

Abstract

We propose a new algorithm for finding the center of a graph, as well as the rank of each node in the hierarchy of distances to the center. In other words, our algorithm allows to partition the graph according to nodes distance to the center. Moreover, the algorithm is parallelizable. We compare the performances of our algorithm with the ones of Floyd-Warshall algorithm, which is traditionally used for these purposes. We show that, for a large variety of graphs, our algorithm outperforms the Floyd-Warshall algorithm.