A parallel vehicle networking modeling method based on small world network theory

A technology of small-world network and modeling method, which is applied in the field of parallel Internet of Vehicles modeling based on the theory of small-world networks, can solve problems such as building parallel Internet of Vehicles, and achieve the effect of improving the level of intelligence and high efficiency

Active Publication Date: 2018-12-21
QINGDAO ACADEMY OF INTELLIGENT IND
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Problems solved by technology

[0005] At present, there is no perfect technology and platform to build a parallel Internet of Vehicles, and related research is still in its infancy. Therefore, we d

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  • A parallel vehicle networking modeling method based on small world network theory
  • A parallel vehicle networking modeling method based on small world network theory
  • A parallel vehicle networking modeling method based on small world network theory

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Embodiment Construction

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention.

[0028] The present invention provides a parallel vehicle networking modeling method based on the small-world network theory, such as figure 1 As shown, the small-world network model constructed by this method can guarantee a shorter average path length and a higher clustering coefficient between any nodes in the network.

[0029] like figure 1 The flowchart shown:

[0030] A parallel vehicle networking modeling method based on the small-world network theory, comprising the following steps:

[0031] Step 1: traverse the node friend list, discover the nodes in the entire network, and construct the original network topology;

[0032] Step 2: Construct an adjacency matrix and generate a network topology map; the specific method is:

[0033]First, construct an N*N adjacency mat...

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Abstract

The invention discloses a parallel vehicle networking modeling method based on small world network theory. Firstly, the network topology is constructed by traversing friends and their friends from a vehicle networking node, and then the network is randomly reconnected according to the small-world network model to form a small-world network with short average path and high clustering coefficient.Finally, the knowledge information is shared through a shortest path communication mode. The method can exchange information with any node in the network with shorter hop count, share the knowledge in the vehicle network with higher efficiency, and improve the intelligent level of the vehicle network. The strategy and algorithm can ensure a better effect, realize the vehicle as an agent to share information like human, can effectively help to establish the vehicle networking ecology, create a huge industrial value, help further extract people, cars, driving habits, service car factory and users.

Description

technical field [0001] The invention relates to a network modeling method, in particular to a parallel vehicle networking modeling method based on the small-world network theory. Background technique [0002] In network theory, a small-world network is a special kind of complex network structure, in which most of the nodes are not connected to each other, but most of the nodes can be reached through a few steps. The small-world phenomenon first appeared in the research experiment on the shortest distance of American social networks in the 1960s. In this experiment, as long as people know the people they know, they can transfer information according to the shortest distance in the social network. to any distance target. The small world network was first introduced by Duncan Watts and Steven Strogatz in 1998. It features high clustering coefficient and low average path length, and proposes a new network model, generally called The Watts-Strogatz model (WS model), which is al...

Claims

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Application Information

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IPC IPC(8): H04W16/22H04L12/24
CPCH04L41/145H04W16/22
Inventor 李玉珂杨林瑶韩双双王晓王飞跃
Owner QINGDAO ACADEMY OF INTELLIGENT IND
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