  Betweenness centrality is a graph parameter that has been successfully
applied to network analysis. In the context of computer networks, it was
considered for various objectives, ranging from routing to service placement.
However, as observed by Maccari et al. [INFOCOM 2018], research on betweenness
centrality for improving protocols was hampered by the lack of a usable, fully
distributed algorithm for computing this parameter. We resolve this issue by
designing an efficient algorithm for computing betweenness centrality, which
can be implemented by minimal modifications to any distance-vector routing
protocol based on Bellman-Ford. The convergence time of our implementation is
shown to be proportional to the diameter of the network
