A research of a strategy to balance the importance and dispersion of multiple critical nodes

Abstract

Maximizing the range of disease or information spread is a hot research topic in complex networks. In particular, the dispersion among a group of nodes and the spreading ability of a single node are two vital factors in the propagation process. However, although some traditional algorithms have considered both factors, they have failed to address the balance between them. To solve this problem, this paper first proposes two metrics to quantify the dispersion of a group of nodes and the local spreading ability of a single node, then designs an objective function fusing these two metrics, which automatically searches for a balance between these two vital factors during the optimization process. We evaluate the proposed algorithm against seven baseline algorithms on three synthetic networks and nine real networks based on the classic susceptible-infected-recovered (SIR) model. Experimental results show that our algorithm is better than some of the centrality-based and heuristic algorithms in the final propagation scale.