Decision tree mechanism-based multi-copy routing method in vehicular Ad hoc networks

Abstract

The present invention discloses a decision tree mechanism-based multi-copy routing method in vehicular Ad hoc networks, and belongs to the technical field of vehicular Ad hoc networks. In the method, a machine is used for learning a learning method in a decision tree C4.5; a vehicle firstly collects historical data, then performs integrated processing on the collected historical data, and performs classification and grading on selected corresponding attributes by using the learning method of the decision tree to generate a decision rule tree; and the constructed decision rule tree is used in transmitting between an initial message and a message copy to enable the transmission of the message to be relatively directional and purposeful. The method is used for solving the problem of overlarge network cost brought from blind flooding retransmission of the message copy number in multi-copy routing, and simultaneously solving the problems of low delivering rate and large time delay as direct transmitting is passively adopted; and compared with a conventional method, the method disclosed by the present invention has higher performances such as timeliness and reliability, and is more suitable for the vehicular Ad hoc networks having high-dynamic topology and a relatively high network density.

Description

technical field [0001] The invention belongs to the technical field of vehicle-mounted self-organizing networks, and relates to a multi-copy routing method based on a decision tree mechanism in the vehicle-mounted self-organizing network. Background technique [0002] Vehicular Adhoc Networks (VANET) is an ad hoc network specially designed for vehicle communication. Due to the continuous high-speed movement of vehicles, the network transmission environment is generally harsh. VANET has attracted much attention in recent years. In VANTE, peer-to-peer communication is very necessary for many applications, including driver assistance systems, Internet access, and collection of road traffic information. Due to the mobility of vehicles, limited wireless resources and lossy wireless channels, it is very challenging to find an efficient path from source node to destination node through a series of intermediate nodes. The efficiency of routing depends on all nodes participating in...

AI Technical Summary

Problems solved by technology

[0006] Although the performance of the above two protocols is good, they also have some defects. For example, the S&W protocol forwards a fixed number of copies, which is not very flexible for application in different networks; in the vehicle ad hoc network, due to Some of its own characteristics, it can obtain various information about the surrounding environment, so the basic protocol can be improved, making it more suitable for application in vehicle ad hoc networks

Moreover, in the second stage, it has been passively waiting to adopt direct transmission or wait until the message reaches the lifetime, which is very unfavorable for the message to be delivered to the destination quickly and effectively

While for the BubbleRap protocol, if all the neighbors of the target node have low network centrality, message delivery will fail

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