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Data routing with machine learning-based routing model

A routing and modeling technology, applied in data exchange networks, digital transmission systems, electrical components, etc., can solve the problems that the selected path cannot meet the required standards and affect the quality of path selection.

Active Publication Date: 2016-09-21
HUAWEI CLOUD COMPUTING TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The accuracy of both the routing model and the network model directly affects the quality of route selection, as an inaccurate model may result in selected routes that do not meet the required criteria

Method used

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  • Data routing with machine learning-based routing model
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  • Data routing with machine learning-based routing model

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Embodiment Construction

[0054] The present invention, in some of its embodiments, relates to apparatus and methods for data routing, and more particularly, but not exclusively, to apparatus and methods for dynamic routing model based data routing.

[0055] Embodiments described herein use machine learning (ML) analysis methods to dynamically develop and maintain network models. The network model is used to route the current and newly requested data streams. The network model is updatable and "evolvable" in the sense that data flows through the data communication network.

[0056] In the embodiments herein, supervised ML is applied to labeled flow routing. In general, supervised machine learning processes a training set containing labeled instances in order to develop models that detect whether new (unlabeled) data conforms to patterns taught by the training set. In embodiments herein, current and / or previous flow routes are stored and marked, where the markings indicate failure or success of a data...

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Abstract

An apparatus for routing data flows through a data communication network includes: a network interface, hardware processor, non-transitory memory, route selection module, analysis module and learning module. The network interface receives requests for routing a flow of data packets within the data communication network. Route selection module routes data flows through the network, based on a routing model applying routing rules to a model of network structure and network parameters. The analysis module determines when routes fail to comply with a respective required level of service (LOS) specifying at least one required performance measure for the flow. Flow routes and their respective failure or success in adhering to the LOS are stored in the routing log. The learning module updates the routing model by processing the routing log, optionally using ML analytics. Optionally, when the model is updated the route selection module reroutes one or more failed flows based on the updated model.

Description

technical field [0001] The present invention, in some of its embodiments, relates to apparatus and methods for data routing, and more particularly, but not exclusively, to apparatus and methods for dynamic routing model based data routing. Background technique [0002] Current methods for routing data through data communications networks use constraint-based routing to select paths for data flows through the network. Constraint-based routing algorithms select routing paths that satisfy constraints, usually guided by routing policies or on a service-oriented basis (eg, Quality of Service (QoS) routing). However, in order to efficiently route data flows without exceeding allocated network resources, an accurate model of the communication network is required. Otherwise, paths may be selected based on outdated or fixed factors, which reduces the effectiveness of the data routing process. Contents of the invention [0003] In embodiments herein, data flows are routed through ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L12/707H04L12/721H04L12/751H04L45/02H04L45/24
CPCH04L45/02H04L45/22H04L45/70
Inventor 哈依姆·珀拉特
Owner HUAWEI CLOUD COMPUTING TECH CO LTD
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