Comprehensive Weighted Clique Degree Ranking Algorithms and Evolutionary Model of Complex Network

Jie Xu,Jun Xu,Zhen Liu

doi:10.1051/matecconf/20167101004

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

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