Abstract

This paper analyses the degree ranking (DR) algorithm, and proposes a new comprehensive weighted clique degree ranking (CWCDR) algorithms for ranking importance of nodes in complex network. Simulation results show that CWCDR algorithms not only can overcome the limitation of degree ranking algorithm, but also can find important nodes in complex networks more precisely and effectively. To the shortage of small-world model and BA model, this paper proposes an evolutionary model of complex network based on CWCDR algorithms, named CWCDR model. Simulation results show that the CWCDR model accords with power-law distribution. And compare with the BA model, this model has better average shortest path length, and clustering coefficient. Therefore, the CWCDR model is more consistent with the real network.

Highlights

  • In recent years, research of complex networks[1,2] become the hot topic in network research

  • We propose a new important node ranking algorithms in complex networks base on clique degree concept, named comprehensive weighted clique degree ranking (CWCDR) algorithm

  • By the simulation in Matlab, we compare the evolutionary network model based on CWCDR algorithm with the BA model, and analyze degree distribution, average shortest path, and clustering coefficient.The results are in the Figure 3

Read more

Summary

Introduction

Research of complex networks[1,2] become the hot topic in network research. Important nodes ranking is always based on degree, betweenness, closeness, etc. These algorithms have different preference characteristics, so different algorithms may reach different results of importance ranking of the nodes[6]. ZHOU proposes the concept of clique degree in his paper[7]. This concept considers the close degree between neighbor nodes, and provides a new way for nodes ranking. Clique degree can be a characterization which can represent the close degree between the nodes, and the clique equals the concept complete subgraph in graph theory. We propose a new important node ranking algorithms in complex networks base on clique degree concept, named comprehensive weighted clique degree ranking (CWCDR) algorithm

Comprehensive weighted clique degree algorithm
Analysis of algorithm
The evolutionary network model
Simulation and Analysis
WCD Model
Conclusions

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.