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Network-key-node self-similar-traffic generation simplification method based on genetic algorithm

A key node and genetic algorithm technology, applied in the field of self-similar traffic generation simplification at key network nodes based on genetic algorithm, can solve problems such as complex traffic input

Active Publication Date: 2014-07-23
BEIHANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The present invention provides a genetic algorithm-based simplified method for generating self-similar traffic at key nodes of the network, with the purpose of solving the problem that the traffic input is too complicated for a specific topology network test or simulation

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  • Network-key-node self-similar-traffic generation simplification method based on genetic algorithm
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  • Network-key-node self-similar-traffic generation simplification method based on genetic algorithm

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Embodiment approach

[0074] Step 1.2, according to the obtained adjacency matrix A((a ij ) n×n ), get the edge node set S and the key node set K, the implementation method is as follows:

[0075] (1) Add each column of A to get the node degree vector V;

[0076] (2) Select the node whose element is 1 in V and store it in S, which is the edge node, with a total of 656 elements;

[0077] (3) Store the node represented by the largest number in V into K, which is the key node, that is, the node with the largest degree.

[0078] In the present invention, the edge node is set as the service source, and its target node is randomly generated in the network. For each edge node S(i) in S, a target node T(j) is randomly selected with equal probability, and the edge node is turned on / off The data generated by the model is sent to the target node along the path Path(i), and the sending path is set according to the network routing mechanism. For example, the shortest path Path(i) of S(i)→T(j) is searched th...

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Abstract

The invention discloses a network-key-node self-similar-traffic generation simplification method based on a genetic algorithm. Network traffic distribution is determined by the mean value and variance of traffic and a self-similar parameter, and at the same time, it is assumed that the network traffic is generated by edge nodes and the same edge node requests the same network service in a traffic generation process. The method includes the following steps: a network typological structure chart is constructed to determine key nodes and the edge nodes; an edge-node on / off model and a mode initial value are constructed; through the genetic algorithm, a parameter optimal solution of the edge-node on / off model is determined; and according to an optimal individual configuration, an optimal parameter is configured at the edge nodes so as to perform simulation and obtain simulating traffic. According to the reality of a current network simulating test, the network-key-node self-similar-traffic generation simplification method takes into consideration that the network traffic is very complicated and time consuming to load according to the practical use conditions of the network traffic and provides a simplified input method to traffic generation of the key nodes and uses the genetic algorithm to find rapidly the optimal solution of a simulating model parameter so that simulation time is saved and simulation efficiency is improved.

Description

technical field [0001] The invention belongs to the technical field of electronic information, relates to a method for generating network traffic based on a genetic algorithm, and specifically provides a simplified method for generating self-similar traffic at a key network node based on a genetic algorithm. Background technique [0002] Research in recent years has shown that the congestion failure of key nodes has a significant impact on the reliability of the entire network system. Generally speaking, a key node is the node with the largest number of nodes connected to it in the network topology. Network congestion fault is a phenomenon in which a large amount of traffic is applied to a network component, causing the stress on the component to continue to exceed its inherent network resource capacity. In reliability analysis, the stress analysis of key nodes is an important content of network performance and reliability research, and the statistical characteristics of tr...

Claims

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Application Information

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IPC IPC(8): H04L12/24
Inventor 黄宁张越伍志韬孙晓磊
Owner BEIHANG UNIV
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