A Method for Ranking the Importance of Command and Communication Network Nodes Based on Complex Networks

In order to address the issue of node importance ranking in command and communication network, the basic principles of complex networks were adopted to propose two basic models: unweighted undirected networks and weighted undirected networks. Three typical structures, namely tree, grid, and hybrid structures, were established, and the importance of nodes is comprehensively quantified using four indicators: degree centrality, betweenness centrality, connectivity, and network efficiency. The experiment shows that the ranking method proposed in the paper can accurately and efficiently identify important nodes, providing a reference for the application and guarantee of command and communication network.

Authors

Institutions

Publication Details

Published
2024-11-29
DOI
https://doi.org/10.1109/irac63143.2024.10871488
Primary Topic
Advanced Research in Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Method for Ranking the Importance of Command and Communication Network Nodes Based on Complex Networks

Cui Pei-zhang, Bing Ji, Jie Tao
Advanced Research in Systems and Signal Processing
article

A Method for Ranking the Importance of Command and Communication Network Nodes Based on Complex Networks

Cui Pei-zhang, Bing Ji, Jie Tao
article en

Abstract

In order to address the issue of node importance ranking in command and communication network, the basic principles of complex networks were adopted to propose two basic models: unweighted undirected networks and weighted undirected networks. Three typical structures, namely tree, grid, and hybrid structures, were established, and the importance of nodes is comprehensively quantified using four indicators: degree centrality, betweenness centrality, connectivity, and network efficiency. The experiment shows that the ranking method proposed in the paper can accurately and efficiently identify important nodes, providing a reference for the application and guarantee of command and communication network.

PLA Army Engineering University (CN)
Openalex Percentile: Top 67%
Advanced Research in Systems and Signal Processing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.