An important node search method based on network diameter
A search method and technology for important nodes, applied in data exchange networks, digital transmission systems, electrical components, etc., can solve problems such as the importance of nodes in special locations that are rarely studied
Active Publication Date: 2019-01-29
DALIAN UNIV OF TECH
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[0006] To sum up, the current research on the importance of nodes in complex networks is often limited to giving each node a specific value in the statistical sense, and there are few methods to study the importance of nodes at special positions from the perspective of network topology.
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[0038] The present invention will be further described below in conjunction with the drawings.
[0039] Such as figure 1 As shown, an important node search method based on network diameter includes the following steps:
[0040] Step 1. Choose a suitable data structure to store the network, and choose adjacency linked list or adjacency matrix;
[0041] Step 2. Define variables and initialize them, including the following sub-steps:
[0042] (a) Initialize the diameter, diameter=0;
[0043] (b) Initialize the queue Q, and use Q to traverse the hierarchy in the subsequent steps;
[0044] (c) Initialize the stack S. In the subsequent steps, the information of the traversal tree whose depth is equal to the diameter is stored in the stack; among them, let the bottom node of the traversal tree be bLNode, and the middle layer node is mLNode. If the diameter is an even number, then the middle layer There is only one layer, if the diameter is odd, the middle layer is two layers;
[0045] (d) Init...
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The present invention relates to an important node search method, an important node search method based on network diameter, comprising the following steps: 1. Select a suitable data structure storage network; 2. Define variables and initialize the variables; 3. Hierarchical traversal storage Hierarchical information, 4. Find the middle layer nodes according to the hierarchical information, 5. Get the midpoint according to the middle layer node information, 6. Comparison of midpoint and non-midpoint centrality indicators, 7. The influence of midpoint and non-midpoint on network diameter 8. Comparison of the impact of midpoint-connected edges and non-midpoint-connected edges on network connectivity. The midpoint searched by the present invention has advantages in betweenness centrality, proximity centrality, degree centrality and k-kernel decomposition, which illustrates the importance of the midpoint in node centrality. After removing the midpoint, the diameter of the network changes significantly, indicating that the midpoint has a great influence on the network topology. After removing the edges connected to the midpoint, the connectivity of the network drops significantly, indicating that the midpoint has a great influence on the connectivity of the network.
Description
Technical field [0001] The invention relates to an important node search method, more specifically, to an important node search method based on network diameter. Background technique [0002] In recent years, extensive research has been conducted at home and abroad on the search of important nodes in complex networks. Different search methods have been applied in actual networks, for example, searching for important proteins in PPI networks. [0003] Node centrality index can be used as an index to measure the importance of nodes. Commonly used centrality indicators include degree centrality, proximity centrality, betweenness centrality and k-core decomposition. The common point of these methods is that each node is assigned a value to indicate the importance of the node under this kind of measurement index, that is, the centrality of the node reflects the importance of the node through statistical information. However, studies have shown that there is often a positive correlatio...
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IPC IPC(8): H04L12/721H04L12/751H04L45/02
CPCH04L45/02H04L45/26
Inventor 关雅文孙媛媛闫俊东
Owner DALIAN UNIV OF TECH