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SDN (Software Defined Networking) self-healing method based on deep learning

A deep learning and network technology, applied in data exchange networks, digital transmission systems, electrical components, etc., can solve problems such as SDN network paralysis, achieve application layer faults and forwarding layer faults, improve operation efficiency, and save network costs. Effect

Active Publication Date: 2017-07-14
ZHEJIANG GONGSHANG UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This control structure realizes the global centralized control of the network. In this case, if a fault occurs and cannot be detected and processed in time, it will lead to the paralysis of the entire SDN network.

Method used

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  • SDN (Software Defined Networking) self-healing method based on deep learning
  • SDN (Software Defined Networking) self-healing method based on deep learning

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Experimental program
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Embodiment Construction

[0030] The present invention will be further described below in conjunction with the accompanying drawings.

[0031] A deep learning-based SDN network self-healing method provided by the present invention provides defense and recovery services for link failures and application failures in the SDN network, including the following steps:

[0032] Add corresponding self-healing modules at each layer of SDN, such as figure 1 Shown:

[0033] The application layer self-healing module includes an application service management module and an application alarm module;

[0034] The control layer self-healing module includes the optimal self-healing module, topology discovery and management module, network statistics module, path management module, policy management module and flow and action management module;

[0035] The forwarding layer self-healing module includes a fast recovery module and an alarm module.

[0036] When an application fault occurs at the application layer, the s...

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Abstract

The invention discloses an SDN (Software Defined Networking) self-healing method based on deep learning. The method comprises the steps that a corresponding self-healing module is added to each layer of an SDN; when an application fault occurs in an application layer, an application layer self-healing module and a control layer self-healing module coordinate and match to solve the fault, and normal operation of the network is recovered; and when a link fault occurs in a forwarding layer, the control layer self-healing module and a forwarding layer self-healing module coordinate and match to solve the fault, and the normal operation of the network is recovered. The invention innovatively provides an SDN self-healing framework. A set of complete self-healing mechanism is designed based on the self-healing framework. The application layer fault and the forwarding layer fault can be processed well. A network structure is optimized, the network cost is saved, the operation efficiency of the network is improved, and defects of the current SDN in self-healing related aspects are compensated.

Description

technical field [0001] The present invention proposes a deep learning-based SDN network self-healing method, which provides defense and recovery services for link failures and application failures in the SDN network. Background technique [0002] With the rapid growth of the Internet scale, the routing and switching equipment at the bottom of the network has reached tens of thousands of units. At the same time, its related network business has become more and more complex. Complicated network services have correspondingly led to various complex network protocols and network management strategies. Debugging the network also becomes increasingly difficult when faults occur in the network. Network protocol factors or human factors may cause different network failures. When the network fails, it will not only affect the user experience and cause the service to be unavailable, but in severe cases, the entire network will be paralyzed. Therefore, ensuring the normal operation ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L12/24H04L12/703H04L12/707H04L12/751H04L12/721H04L12/741H04L45/02H04L45/24H04L45/28H04L45/74
CPCH04L41/0631H04L41/0654H04L45/02H04L45/123H04L45/22H04L45/28H04L45/74
Inventor 周静静鹿如强张胜龙王伟明郑月燃
Owner ZHEJIANG GONGSHANG UNIVERSITY
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