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

翻译：在计算机网络方面,它被考虑用于从路线到服务布置等各种目标。然而,正如Macccari等人[INFOCOM 2018]所指出的,关于改进协议之间的中心点的研究由于缺乏计算该参数的可用和完全分布的算法而受阻。我们通过设计一个计算中心点的有效算法来解决这个问题,可以通过对Bellman-Ford基础上的任何距离-摄像路由协议进行最低限度的修改来实施。我们执行的合并时间与网络的直径成正比。