A complexity measure for military communication networks

Fu-li, Shi; Li, Chao; Qin, Dongliang; Zhu, Yifan; Yang, Feng

doi:10.1109/milcom.2011.6127557

Cited by 6 publications

(4 citation statements)

References 19 publications

(11 reference statements)

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“…Xiong Jinshi [6] , based on the examples of military communication network, finds that the communication network has higher aggregation coefficient and smaller average path length, which is in line with the characteristics of small-world network. Based on this, he built the topology of military communication network.…”

Section: Command Information System Network Topological Modelmentioning

confidence: 63%

Network connectivity analysis of command information system based on link heterogeneity

Zheng,

Sun

2024

International Conference on Communication, Information, and Digital Technologies (CIDT2024)

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Because the complex network modeling link of traditional command information system is single, it can not reflect the heterogeneity of network link, nor can it qualitatively and quantitatively analyze the influence of electronic interference on the connectivity of command information system, a new command information system modeling method introduced into the military communication network. The communication network is divided into wired communication subnet and wireless communication subnet to solve the problem of link heterogeneity. Meanwhile, the influence of electronic interference on network connectivity can be qualitatively and quantitatively analyzed. The connectivity of command information system network attacked by random interference edge, random interference node and node degree attack is simulated and analyzed. The results show that this new mode of command information system modeling can qualitatively and quantitatively analyze the connectivity of command information system under soft weapon attack, which is more suitable for operational practice.

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Section: Command Information System Network Topological Modelmentioning

confidence: 63%

Network connectivity analysis of command information system based on link heterogeneity

Zheng,

Sun

2024

International Conference on Communication, Information, and Digital Technologies (CIDT2024)

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“…Supernetwork Motif Entropy (SNME) is a complexity measure combining the heterogeneity of nodes, the significance of functional motifs and information entropy for military communication networks (MCN). It is presented by Shi et al [36]. The mathematical representation is…”

Section: ) Snmementioning

confidence: 99%

A Survey of Measures for Network Motifs

Xia

Wei

et al. 2019

IEEE Access

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Network motifs provide an enlightening insight into uncovering the structural design principles of complex networks across multifarious disciplines, such as physics, biology, social science, engineering, and military science. Measures for network motifs play an indispensable role in the procedures of motif measurement and evaluation which are crucial steps in motif detection, counting, and clustering. However, there is a relatively small body of literature concerned with measures for network motifs. In this paper, we review the measures for network motifs in two categories: structural measures and statistical measures. The application scenarios for each measure and the distinctions of measures in similar scenarios are also summarized. We also conclude the challenges for using these measures and put forward some future directions on this topic. Overall, the objective of this survey is to provide an overview of motif measures, which is anticipated to shed light on the theory and practice of complex networks.INDEX TERMS Network motif, motif measure, network science and motif definition.

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“…However, the applicability of these models to real-world problems was not clearly indicated in their studies. Zhao et al [21] constructed a three-layer supernetwork model for weapon system-of-systems (WSoS) based on task-capability relationships, while Shi et al [22] proposed specific procedures for network evolution in three-layer military communication supernetworks. Although the abovementioned models provide an effective description of the multilevel characteristics of C2 networks, the connections between fine-grained nodes are expressed using complex network theory, which has inherent limitations in describing multimodal relationships.…”

Section: Introductionmentioning

confidence: 99%

Multilevel Command and Control Supernetwork Modeling Based on Attribute Synergy Prioritization

Chen

Wang

et al. 2019

IEEE Access

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Current command and control (C2) network models typically do not account for differences in attributes of nodes that belong to the same class; in addition, there is no provision in these models for the adequate description of operational relationships that exist between multiple combat entities with different attributes in real-world scenarios. To address these issues, we propose a method to model multilevel command and control supernetworks (MC 2 S) based on the attribute synergy prioritization and hypergraph theory. First, the characteristics of C2 supernetworks are analyzed to abstract their nodes and hyperedges, based on which, we propose the MC 2 S model, which consists of three layers and five networks. Second, the Term Frequency-Inverse Document Frequency and spatial distance algorithms are used to construct an attribute synergy prioritization-based strategy for the generation of intra-layer MC 2 S hyperedges, while the local-world (LW) selection is used to create an LW model-based method for the generation of inter-layer MC 2 S hyperedges. Through simulation experiments, we show that our model exhibits (approximately) scale-free properties as well as small-world properties, excellent cooperative engagement capabilities, and has a high level of network invulnerability. These findings will serve as a useful reference for the description of complex nodal (edge) relationships in C2 networks, network performance analyses, and deployment of complex combat mission networks. INDEX TERMS Attribute synergy prioritization, command and control, hypergragh, supernetwork modeling.

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A complexity measure for military communication networks

Cited by 6 publications

References 19 publications

Network connectivity analysis of command information system based on link heterogeneity

Network connectivity analysis of command information system based on link heterogeneity

A Survey of Measures for Network Motifs

Multilevel Command and Control Supernetwork Modeling Based on Attribute Synergy Prioritization

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