System Science

Jodhpur, India

System Science

Jodhpur, India
SEARCH FILTERS
Time filter
Source Type

Kumar pandey P.,System Science | Adhikari B.,Indian Institute of Technology Kharagpur
IEEE Transactions on Knowledge and Data Engineering | Year: 2017

We propose a parametric network generation model which we call network reconstruction model (NRM) for structural reconstruction of scale-free real networks with power-law exponent greater than 2 in the tail of its degree distribution. The reconstruction method for a real network is concerned with finding the optimal values of the model parameters by utilizing the power-law exponents of model network and the real network. The method is validated for certain real world networks. The usefulness of NRM in order to solve structural reconstruction problem is demonstrated by comparing its performance with some existing popular network generative models. We show that NRM can generate networks which follow edge-densification and densification power-law when the model parameters satisfy an inequality. Computable expressions of the expected number of triangles and expected diameter are obtained for model networks generated by NRM. Finally, we numerically establish that NRM can generate networks with shrinking diameter and modular structure when specific model parameters are chosen. IEEE

Loading System Science collaborators
Loading System Science collaborators