Topology evolution model for wireless multi-hop network based on socially inspired mechanism

In this paper, topology evolution problem is addressed for improving the network performance in wireless multi-hop networks. A novel topology model based on social inspired mechanism with energy-aware and local-world features is proposed to handle the time-varying nature of wireless multi-hop network. A series of theoretical analysis and numerical simulation to the social inspired evolution network are conducted. Firstly, the degree distribution of this social inspired model represents a transition between exponential to power-law scaling with increasing the local world scale. Secondly, the clustering coefficient and the average path length decrease sharply as generally local-world scale increases a little. Finally, we found that the robustness and fragility of the proposed network model against random failures and attacks also display a transition between the random and the scale-free ones when the scale of local-world increasing. This local-world social inspired network model can maintain the robustness of scale-free networks and can improve the network reliance against intentional attacks.