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Environment adaptive routing method and system based on Bayesian classification and medium

A Bayesian classification and self-adaptive technology, applied in the field of communication, can solve problems such as the difficulty of detecting and maintaining a dynamically changing network environment, insufficient self-adaptive adjustment capabilities of data distribution strategies, and insufficient ability to adjust the degree of rational node cooperation. Real-time perception ability, improving self-adaptive adjustment ability, enhancing self-adaptability and the effect of

Active Publication Date: 2021-08-24
SHANDONG WOMENS UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, for distributed mobile environments and mobile devices with scarce resources, it is very difficult to detect and maintain a dynamically changing network environment
The real-time perception ability of the network environment directly affects the node's judgment of the network environment, thereby affecting the efficiency of the data distribution strategy
[0007] (2) Insufficient cooperation adjustment ability of rational nodes
[0009] (3) Insufficient adaptive adjustment ability of data distribution strategy

Method used

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  • Environment adaptive routing method and system based on Bayesian classification and medium
  • Environment adaptive routing method and system based on Bayesian classification and medium
  • Environment adaptive routing method and system based on Bayesian classification and medium

Examples

Experimental program
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Effect test

Embodiment 1

[0038] Embodiment one, as figure 1 As shown, an environment adaptive routing method based on Bayesian classification, including the following steps:

[0039]S1: Construct a dynamic network environment learning model of the social perception network, use the dynamic network environment learning model to perform dynamic perception on each node in the social perception network, and obtain a dynamic perception information set of each node;

[0040] S2: Select any pair of meeting nodes in the social perception network, and based on the Bayesian classification method, according to the dynamic perception information sets of the two meeting nodes in the selected meeting node pair, obtain the distance between the two selected meeting nodes The cooperation type vector and the one-to-one correspondence cooperation degree information set of two meeting nodes;

[0041] S3: According to the preset adaptive data distribution strategy, according to the dynamic perception information set and ...

Embodiment 2

[0138] Embodiment two, such as Figure 8 As shown, an environment adaptive routing system based on Bayesian classification is applied to the environment adaptive routing method based on Bayesian classification in Embodiment 1, including a modeling perception module, a cooperative judgment module, and an adaptive distribution module and the traversal module;

[0139] The modeling perception module is used to construct a dynamic network environment learning model of the social perception network, and uses the dynamic network environment learning model to perform dynamic perception on each node in the social perception network respectively, and obtain the dynamic perception of each node information set;

[0140] The cooperation judgment module is used to select any pair of encounter nodes in the social perception network, and based on the Bayesian classification method, according to the dynamic perception information sets of the two encounter nodes in the selected encounter node...

Embodiment 3

[0176] Embodiment 3. Based on Embodiment 1 and Embodiment 2, this embodiment also discloses an environment adaptive routing system based on Bayesian classification, which includes a processor, a memory, and is stored in the memory and can run on the A computer program on the processor, the specific steps of S1 to S4 are implemented when the computer program runs.

[0177] By storing computer programs on the memory and running them on the processor, data distribution in the dynamic social perception network can be realized, which can effectively improve the self-awareness of the dynamically changing network environment, enhance the self-adaptability and cooperation degree of the data distribution strategy The self-regulation of the incentive mechanism, which in turn significantly improves the data distribution efficiency in the social perception network, has important application value.

[0178] This embodiment also provides a computer storage medium, where at least one instruc...

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Abstract

The invention relates to an environment adaptive routing method and system based on Bayesian classification and a medium, and the method comprises the steps: constructing a dynamic network environment learning model, and carrying out the dynamic perception of each node, and obtaining a dynamic perception information set of each node; selecting any encountering node pair, and obtaining a cooperation type vector between the two encountering nodes and cooperation degree information sets corresponding to the two encountering nodes one by one according to the dynamic sensing information sets of the two encountering nodes based on a Bayesian classification method; according to a preset adaptive data distribution strategy, completing data distribution of the two encountering nodes according to the dynamic sensing information set, the cooperation degree information set and the cooperation type vector of the two encountering nodes; and traversing each encountering node pair to complete data distribution of the social perception network. According to the method, the self-perception of a dynamic change network environment is effectively improved, the self-adaptability of a data distribution strategy and the self-adjustability of a cooperation degree incentive mechanism are enhanced, and the data distribution efficiency is remarkably improved.

Description

technical field [0001] The present invention relates to the field of communication technology, in particular to an environment adaptive routing method, system and medium based on Bayesian classification. Background technique [0002] With the advent of the era of networking and intelligence, mobile networking devices have become popular, and multi-network integration has become a trend in network development. Opportunistic networks do not require the support of infrastructure and rely on the cooperation between nodes to achieve communication, which is a powerful supplement for future multi-network integration. Opportunistic networks have mature applications in many fields, such as wildlife tracking, communication in remote areas, and networking of handheld devices. The improvement of the performance of handheld mobile devices, their popularity in social life, and the support of the next-generation communication network 5G enable mobile devices to obtain more data with chara...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W40/02H04W40/24G06K9/62
CPCH04W40/02H04W40/248G06F18/24155Y02D30/70
Inventor 刘丽
Owner SHANDONG WOMENS UNIV
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