Research of Edge Centrality Based on the Algebraic Connectivity

In connected graph, edge centrality represents the importance of edge and loading degree in the process of information transmission. The second eigenvalue of Laplacian matrix decides connectivity of complex networks. We propose edge centrality model and cut model based on minimization model of the algebraic connectivity. Edge centrality function is derived in order to calculate edge centrality. Cut model deletes k edges at an iteration whose algebraic connectivity of complex networks decreased fastest. Choice of k is based on edge sparse degree of complex networks. By empirical analysis of real network, the implications of edge with higher centrality and its vertex coincide with the fact. The model can be used in medium-size networks with lower time complexity and higher efficiency.