Caveman network and its application in analysis of complex network entropy

Entropy can effectively reflect the network structure heterogeneity of complex systems. For the question of applicability of entropy indices to describe the global heterogeneity of the network, the benchmark networks for the evaluation are still lacking. On the foundation of previous study, this paper introduces a Caveman network and its evolution rules, which provides a new way of thinking for measurement of network complexity. The theoretical analysis and simulation experiments indicate that the Caveman network can effectively evaluate the sensitivity of different structure entropies on evolution process of Caveman network, and reflect the difference of ability to identify the properties of network complex of entropy indices. Besides that, Caveman network can promote exploration in information space and resist network attacks, shedding new light on designing system structure with high robustness and efficiency.