Estimating the Degree Centrality Ranking of a Node
Social and Information Networks
2019-10-08 v2 Physics and Society
Abstract
Complex networks have gained more attention from the last few years. The size of real-world complex networks, such as online social networks, WWW network, collaboration networks, is increasing exponentially with time. It is not feasible to collect the complete data and store and process it. In the present work, we propose a method to estimate the degree centrality rank of a node without having the complete structure of the graph. The proposed algorithm uses the degree of a node and power-law exponent of the degree distribution to calculate the ranking. Simulation results on the Barabasi-Albert networks show that the average error in the estimated ranking is approximately of the total number of nodes.
Cite
@article{arxiv.1511.05732,
title = {Estimating the Degree Centrality Ranking of a Node},
author = {Akrati Saxena and Vaibhav Malik and S. R. S. Iyengar},
journal= {arXiv preprint arXiv:1511.05732},
year = {2019}
}