Co-evolution Modeling Method Based On The Multilayer Complex Network Constrained Growth

With the emergency of complex network research in recent years, more and more people focus their attention on the network modeling. ER random graph,small world and scale-free model explain different phenomena of real world. Among them,B A scale-free model accounts for the phenomena of distribution of power law real world. It emphasized two characteristics of network:growth and preferential attachment features. Following the BA model,researches proposed fitness model,local world evolving network model,which all optimize the origin model.This article draw on related model of complex network and refer to the characteristic of them on growth and preferential attachment.Then we propose our model combining the properties of real world. Compared to other model, our model is based on a constrained network. Most of models begin to build their network from an empty network. However, the proposed model in this article is based on the underlying constraint network, which is a limited growth model. The reason why we consider the constraint network is that most of real network often grow under some frame.Considering different factors effecting the execution network,we mainly experiment from following directions:analysis the influence of different topology on execution network,such as, different power-law BA scale-free network,different rewiring probability small world and different connecting probability;considering the strength of constraint-simulating it by different deleting edge probability; the influence of growth pattern-different weight network;different growth speed between constraint network and execution network.