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A Supernetwork-based Hierarchical Evolution Method for Command and Control Network

A network layered and super-network technology, applied in the field of command and control network modeling, can solve problems such as network integration and single evolution, and achieve the effect of multiple node functions, high command efficiency, and small average distance

Active Publication Date: 2019-04-19
DALIAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Aiming at the problem of single evolution in some existing network models, it is difficult to integrate with the network in the real world. This application provides a layered evolution method of the accusation network based on the supernetwork, which makes the commanding efficiency of the accusation network higher and the inter-node Better connectivity, stronger organizational structure reliability, and more node functions

Method used

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  • A Supernetwork-based Hierarchical Evolution Method for Command and Control Network
  • A Supernetwork-based Hierarchical Evolution Method for Command and Control Network
  • A Supernetwork-based Hierarchical Evolution Method for Command and Control Network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0032] This embodiment provides a method for hierarchical evolution of accusation network based on supernetwork, which specifically includes:

[0033] Step 1: Abstract the relationship between nodes in the accusation network:

[0034] The nodes of the command and control network can be divided into three levels according to their functions, including the perception layer, command layer, and firepower layer. Nodes are abstracted into supernodes in the hypernetwork, and the connections between nodes are abstracted into hyperedges in the network. The command node often needs to receive information from multiple intelligence nodes and command multiple firepower nodes. A hyperedge can be used to connect the relevant intelligence nodes, firepower nodes and command nodes to form a set of combat relationships; at the same time, between command nodes, firepower There is also information interaction between nodes and between sensing nodes. Several nodes are connected by a hyperedge to ...

Embodiment 2

[0039] As a further limitation to Embodiment 1, the construction process of the layered evolution model of the accusation supernetwork is as follows:

[0040] Step 1, initialization: there is already a hyperedge, connecting m nodes;

[0041] Step 2, increase the network nodes: at the nth layer time step t n , and 1≤n≤K, select a node from the existing network nodes according to the probability P(i), and use a hyperedge to connect this node with the newly added M n node connection;

[0042] The connection probability P(i) of selecting node i each time is equal to the hyperdegree d of node i H (i) The ratio to the sum of the hyperdegrees of existing nodes in the hypernetwork, the formula is:

[0043]

[0044] Step 3, layer transformation: when the nth layer new node increases C n After the number of times, enter the (n+1) layer modeling, and the number of nodes added each time in the (n+1) layer becomes M (n+1) , the number of increments in this layer becomes C (n+1) Seco...

Embodiment 3

[0047] The verification of the hierarchical evolution network model constructed in Example 2 is as follows: In order to ensure the accuracy of the experimental results and make the experimental results comparable, the number of nodes is selected to be about 60,000, and the simulation results are the average of 10 experiments. In the initial state, it consists of 3 supernodes and 1 hyperedge, each additional node is connected to one of the existing nodes, and so on. This group of experiments consisted of one-layer network model, that is, the conventional hyper-network model and the 5-layer network model. Through simulation modeling, the hyper-degree distribution of the model was counted, and the statistical distribution was obtained as follows: image 3 and 4 shown. The experimental data are specifically: {K=1, M n = 3, C n =20000}, a total of 60003 nodes and 20000 hyperedges are generated, such as image 3 ;{K=5,M n = [2, 5, 7, 9, 13], C n =[760, 960, 1140, 1800, 2280]},...

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Abstract

The invention discloses a supernet-based command and control network hierarchical evolution method, which specifically comprises the steps of: step 1, abstracting relationships among nodes of a command and control network; step 2, constructing a command and control supernet hierarchical evolution model; step 3, and simulating the constructed hierarchical evolution model, and verifying network characteristics thereof. The supernet-based command and control network hierarchical evolution method has the advantages that command efficiency of the command and control network is higher, connectivity among the nodes is better, reliability of the organization structure is higher, and more functions of the nodes are achieved.

Description

technical field [0001] The invention belongs to the field of command and control network modeling, in particular to a layered evolution method of command and control network based on supernetwork. Background technique [0002] With the wide application of communication and network technologies in modern local wars, information warfare has gradually become a new way of fighting on the battlefield; The construction of the control network puts forward higher requirements, making the command and control network as the carrier of information transmission play a pivotal role. [0003] Because the command and control network has the characteristics of node heterogeneity, multiple links and time-varying topology, it is difficult for the traditional network structure model based on classical graph theory to accurately describe its structure and functional characteristics, and the traditional network analysis method is difficult to reflect its military application characteristics. As...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L12/24
CPCH04L41/145
Inventor 王运明张冬陈波潘成胜
Owner DALIAN UNIV
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