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Internet of vehicles node forwarding utility learning method based on double-update strategy

A node forwarding and learning method technology, which is applied in the direction of specific environment-based services, machine learning, and vehicle components, can solve the problems of sparse node distribution, rapid network topology changes, and difficulty in promoting the Internet of Vehicles, and achieve the goal of improving transmission performance Effect

Active Publication Date: 2021-11-30
HARBIN ENG UNIV +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the practical application of highly dynamic ad hoc network / vehicle networking, it often faces the problems of sparse distribution of nodes in the city and rapid changes in network topology, which cannot guarantee the connectivity of the network. Therefore, the traditional mobile ad hoc network communication protocol is no longer suitable for these complex Scenes
Because the condition for the application of these traditional communication protocols is to ensure that there is no less than one end-to-end link between any pair of nodes in the network, and this condition is difficult to be satisfied in the actual ad hoc network, so it is difficult to ensure that the network The transmission performance of the Internet of Vehicles makes it difficult to promote the Internet of Vehicles in practical applications.

Method used

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  • Internet of vehicles node forwarding utility learning method based on double-update strategy
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  • Internet of vehicles node forwarding utility learning method based on double-update strategy

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specific Embodiment 1

[0067] according to Figure 3 to Figure 10 As shown, the present invention provides a kind of vehicle networking node forwarding utility learning method based on double updating strategy, a kind of vehicle networking node forwarding utility learning method based on double updating strategy, comprises the following steps:

[0068] Step 1: Based on the information update during the information interaction process between vehicle nodes, determine the basic elements in the learning process;

[0069] The step 1 is specifically:

[0070] Determine the basic elements needed in the learning process, the elements include: environment, agent, state space, action space and immediate return; define node update information table, the node update information table includes node contact information table and node state- action value table;

[0071] The environment provides the required information for the entire vehicular opportunistic network in the city as the data packets are forwarded ...

specific Embodiment 2

[0115] attached image 3 Shown is the overall framework of the forwarding utility learning model design process in the present invention. Node opportunistic contact is the premise of on-board opportunistic network packet forwarding, and also a necessary condition for node forwarding utility update. Node contact can update the contact freshness coefficient and contact probability between node pairs, and the contact freshness coefficient can be used to dynamically adjust the freshness of node contact probability; the key components of the update formula of the forwarding utility learning model include node contact probability, immediate Reward function and dynamic discount factor; the learning process of forwarding utility mainly includes the use of Q learning strategy to realize the learning of data packets in the process of transmitting data packets between nodes in the vehicle-mounted opportunistic network and the learning in the process of node contact, using the forwarding ...

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Abstract

The invention relates to an Internet of Vehicles node forwarding utility learning method based on a double-update strategy. The invention relates to the technical field of mobile opportunity network communication, wherein the method comprises the steps: determining basic elements in a learning process based on information updating in an information interaction process between vehicle nodes; determining a node contact freshness coefficient, determining a node contact probability, and establishing a node forwarding first-use learning model in the vehicle-mounted opportunity network; determining a forwarding utility learning updating model according to the routing requirement of the vehicle-mounted opportunity network and the opportunity contact characteristic of the node, establishing a forwarding utility value data packet forwarding updating strategy, obtaining the moment when the sending node receives the data packet from the previous node, and establishing a forwarding utility value node contact updating strategy, wherein a learning coefficient different from a forwarding updating process is adopted in the updating process. According to the invention, the transmission performance of the vehicle-mounted opportunity network is improved, including improving the data packet delivery success rate and reducing the data packet transmission delay.

Description

technical field [0001] The invention relates to the technical field of mobile opportunistic network communication, and is a method for learning the forwarding utility of a vehicle networking node based on a double update strategy. Background technique [0002] The development wave of industrial automation promotes the development of high-tech such as information sensing, data communication and data processing. Monitoring, wild animal migration tracking and many other fields, social development has gradually entered the information age of the Internet of Things. In order to meet the ubiquitous interconnection and comprehensive perception requirements of the Internet of Things / Internet of Vehicles, smart devices need to be networked and interconnected. Therefore, the networking technology between devices has increasingly become the focus of the Internet of Things research field. In the practical application of highly dynamic ad hoc network / vehicle networking, it often faces t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L12/751H04W4/46H04W40/24G06N20/00G06Q50/30H04L45/02
CPCH04W4/46H04L45/08H04W40/248G06N20/00G06Q50/40Y02D30/70
Inventor 王桐王希波刘逸伦高山曹越
Owner HARBIN ENG UNIV
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