A method and system for selecting key nodes in a communication network
A key node and communication network technology, applied in the field of network management, can solve the problems of small comprehensive influence of nodes, overlapping influence ranges, and large overlapping influence of key nodes, so as to improve the comprehensive influence, prevent virus or information dissemination, The effect of controlling the spread of viruses or information
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment 1
[0061] Embodiment 1 of the present invention provides a method for selecting key nodes in a communication network.
[0062] Such as figure 1 As shown, the selection method includes the following steps:
[0063] Step 101, determine the adjacency matrix of the original network; step 102, calculate the influence of each node in the original network according to the adjacency matrix and the overlapping influence algorithm based on Rayleigh entropy; step 103, select the most influential node as a key node, and add the key node to the set of key nodes; step 104, judge whether the number of key nodes is less than a preset threshold; step 105, if the number of key nodes is less than a preset threshold, delete the original The edge passing through the key node in the network is obtained the updated original network, and according to the updated original network, the adjacency matrix is updated; the return step "according to the adjacency matrix, the overlap influence based on Raylei...
Embodiment 2
[0065] Embodiment 2 of the present invention provides a preferred implementation manner of a method for selecting a key node in a communication network, but the implementation of the present invention is not limited to the implementation manner defined in Embodiment 2 of the present invention.
[0066] Such as figure 2 as shown,
[0067] The data preprocessing of the original network is preferred. If it is a directed weighted graph, the direction and weight of the edge are ignored. Since the nodes in different subgraphs do not transmit information to each other, the isolated nodes and isolated clusters in the network are deleted at the same time. .
[0068] Then, the determination of the adjacency matrix of the original network specifically includes
[0069] The input original network is expressed as an adjacency matrix A={a ij} N×N , where a ij is the element value of the position of the adjacency matrix A(i, j), indicating the weight between node i and node j, when the...
Embodiment 3
[0085] Embodiment 3 of the present invention provides a method for verifying the effectiveness of a method for selecting key nodes in a communication network.
[0086] Take the key node selection algorithm based on node degree as an example:
[0087] Calculate the degree of each node separately.
[0088] Sort the degree of each node.
[0089] Select the first two nodes as key nodes, such as image 3 b According to the algorithm, we can know that the key nodes are 4 and 6.
[0090] Take the key node selection algorithm based on Rayleigh entropy as an example:
[0091] According to the node importance formula S m = d m ∑ j,k a mj a jk d k +∑ j,k a jm a mk d j d k Calculate the importance of each node.
[0092] Select the node with the highest node importance and delete the edges connected to this node.
[0093] Repeat (1), (2) until two key nodes are selected. Such as image 3 a According to the algorithm, it can be known that the key nodes are 1, 6;
[0094] ...
PUM
Login to View More Abstract
Description
Claims
Application Information
Login to View More 


