Overlay network routing decision-making method based on deep learning

An overlay network and deep learning technology, applied in real-time interactive video stream transmission scenarios, in the field of overlay network routing decision-making based on deep learning, can solve problems such as inability to predict current node parameters well, large amount of calculation, and game player delays. Achieve the effect of ensuring the effect of routing decision-making, improving speed and quality, and improving decision-making response speed

Active Publication Date: 2020-04-14
NANJING UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In cloud game application scenarios, if the network delay is greater than 50ms, 70% of gamers will feel obvious delay
Additionally, the underlying routing path from the hosting game server to the user will experience high network latency if network congestion occurs in the underlying routing path
If the underlying routing connection fails, the cloud game service will experience a long recovery time, which will greatly affect the quality of experience
[0003] At the same time, for the traditional routing decision-making method (bottom routing selection), in the process of routing path sele

Method used

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  • Overlay network routing decision-making method based on deep learning
  • Overlay network routing decision-making method based on deep learning
  • Overlay network routing decision-making method based on deep learning

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Embodiment Construction

[0022] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0023] In this embodiment, the method of the present invention is applied in a cloud game application scenario.

[0024] refer to figure 1 , an overlay network routing decision method based on deep learning, including the following steps:

[0025] S1, deploy and cover 10 overlay network routing nodes between the user and the cloud game server, the order is x 1, x 2 ,...,x 10 , at the current t i Collect the bandwidth matrix B between the coverage routing nodes at any time:

[0026]

[0027] any of them Indicates the overlay network routing node x i to overlay network routing node x j bandwidth between

[0028] Delay matrix D between two covering routing nodes:

[0029]

[0030] any of them Indicates the overlay network routing node x i to overlay network routing node x j time delay between

[0031] At this point, the raw...

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Abstract

The invention discloses an overlay network routing decision-making method based on deep learning. The method comprises the following specific steps: S1, deploying overlay network routing nodes, and collecting a bandwidth time delay change data set; S2, making a data set for training, wherein the data set comprises a prediction network data set and a classification network data set selected by thecoverage routing node, the label of the prediction network is the time delay and bandwidth data of the next moment, and the label calculation mode of the classification network selected by the coverage routing node is obtained by calculation on the coverage network topology formed by the coverage network routing node by adopting a shortest path algorithm; S3, constructing a bandwidth delay prediction network based on a recurrent neural network LSTM and a coverage routing node selection classification network for coverage routing node selection; S4, training and optimizing a deep learning model; and S5, making a decision through the model. According to the method, the decision response speed can be greatly improved while the routing decision effect is ensured, especially when the scale of coverage network nodes is huge.

Description

technical field [0001] The invention relates to the fields of computer network and video transmission, in particular to a real-time interactive video stream transmission scene with high transmission delay requirements, and in particular to an overlay network routing decision method based on deep learning. Background technique [0002] With the development of the Internet, online entertainment has widely penetrated into people's daily life. Moreover, with the interactive attributes of online social entertainment, the user's quality of experience is highly related to network delay. In a cloud gaming application scenario, if the network delay is greater than 50ms, 70% of gamers will feel an obvious delay. Additionally, the underlying routing path from the hosting game server to the user will experience high network latency if network congestion occurs in the underlying routing path. If the underlying routing connection fails, the cloud game service will experience a long reco...

Claims

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Application Information

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IPC IPC(8): H04L12/721H04L12/727H04L12/751H04L29/06H04L29/08H04L45/02H04L45/121
CPCH04L45/121H04L45/14H04L45/02H04L67/10H04L45/08H04L67/131
Inventor 张旭许刘泽赵阳超杨凯马展
Owner NANJING UNIV
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