Parallel Algorithm for Incremental Betweenness Centrality on Large Graphs
نویسندگان
چکیده
منابع مشابه
Further Results on Betweenness Centrality of Graphs
Betweenness centrality is a distance-based invariant of graphs. In this paper, we use lexicographic product to compute betweenness centrality of some important classes of graphs. Finally, we pose some open problems related to this topic.
متن کاملBetweenness Centrality - Incremental and Faster
We present an incremental algorithm that updates the betweenness centrality (BC) score of all vertices in a graph G when a new edge is added to G, or the weight of an existing edge is reduced. Our incremental algorithm runs in O(ν∗ · n) time, where ν∗ is bounded by m∗, the number of edges that lie on a shortest path in G. We achieve the same bound for the more general incremental vertex update ...
متن کاملTowards Improving Brandes' Algorithm for Betweenness Centrality
Betweenness centrality, measuring how many shortest paths pass through a vertex, is one of the most important network analysis concepts for assessing the (relative) importance of a vertex. The famous state-of-art algorithm of Brandes [2001] computes the betweenness centrality of all vertices in O(mn) worst-case time on an n-vertex and m-edge graph. In practical follow-up work, significant empir...
متن کاملIncremental Deployment of Network Monitors Based on Group Betweenness Centrality
Shlomi Dolev, Yuval Elovici, Rami Puzis, Polina Zilberman Abstract In many applications we are required to increase the deployment of a distributed monitoring system on an evolving network. In this paper we present a new method for finding candidate locations for additional deployment in the network. This method is based on the Group Betweenness Centrality (GBC) measure that is used to estimate...
متن کاملA Faster Algorithm for Betweenness Centrality
The betweenness centrality index is essential in the analysis of social networks, but costly to compute. Currently, the fastest known algorithms require Θ(n) time and Θ(n) space, where n is the number of actors in the network. Motivated by the fast-growing need to compute centrality indices on large, yet very sparse, networks, new algorithms for betweenness are introduced in this paper. They re...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Parallel and Distributed Systems
سال: 2018
ISSN: 1045-9219
DOI: 10.1109/tpds.2017.2763951