Distributed Algorithms for Directed Betweenness Centrality and All Pairs Shortest Paths
Abstract
The betweenness centrality (BC) of a node in a network (or graph) is a measure of its importance in the network. BC is widely used in a large number of environments such as social networks, transport networks, security/mobile networks and more. We present an O(n)-round distributed algorithm for computing BC of every vertex as well as all pairs shortest paths (APSP) in a directed unweighted network, where n is the number of vertices and m is the number of edges. We also present O(n)-round distributed algorithms for computing APSP and BC in a weighted directed acyclic graph (dag). Our algorithms are in the Congest model and our weighted dag algorithms appear to be the first nontrivial distributed algorithms for both APSP and BC. All our algorithms pay careful attention to the constant factors in the number of rounds and number of messages sent, and for unweighted graphs they improve on one or both of these measures by at least a constant factor over previous results for both directed and undirected APSP and BC.
Cite
@article{arxiv.1805.08124,
title = {Distributed Algorithms for Directed Betweenness Centrality and All Pairs Shortest Paths},
author = {Matteo Pontecorvi and Vijaya Ramachandran},
journal= {arXiv preprint arXiv:1805.08124},
year = {2019}
}
Comments
The new algorithms for APSP and BC in Section 4 of this manuscript will appear as the theoretical component in the following paper, which will appear in Proc. ACM PPoPP, February 2019: Loc Hoang, Matteo Pontecorvi, Roshan Dathathri, Gurbinder Gill, Bozhi You, Keshav Pingali, and Vijaya Ramachandran - A round-efficient distributed Betweenness Centrality algorithm