YANG Model Self-Explanation Tag for SDN Device Management
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Solution Overview
Problem
In software-defined networks (SDNs), as the scale of devices increases and more services are carried, there is a need for intelligent operation and maintenance that detects microburst traffic quickly and precisely, while minimizing the impact on device functions and performance, which existing technologies struggle to achieve efficiently.
Innovation Solution
A device management method using an extended YANG model file with a self-explanation tag to label network operation and maintenance data, facilitating accurate and efficient data collection and management by determining XPATH paths and generating network element driver packages based on the self-explanation tag and mechanism capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional monitoring methods are used in SDN networks, then device scale can increase, but monitoring precision deteriorates and microburst traffic cannot be detected quickly
Solution Approach 1:
The patent segments the monitoring system into multiple independent monitoring devices distributed across the SDN network. Each monitoring device independently collects and analyzes traffic data from specific network segments, enabling parallel processing of monitoring tasks. This segmentation allows the system to maintain high monitoring precision across the entire network while reducing detection time through concurrent operations, directly resolving the contradiction between monitoring precision and detection speed.
Solution Approach 2:
The patent implements preliminary action by pre-configuring monitoring devices with collection capabilities and establishing monitoring subscriptions before microburst traffic occurs. The system proactively sets up data collection paths, XPATH expressions, and subscription mechanisms in advance, so when abnormal traffic patterns emerge, the monitoring devices can immediately begin high-precision detection without configuration delays. This preliminary preparation resolves the contradiction by ensuring both precision and speed are available when needed.
2Speed
If comprehensive monitoring is implemented to detect microburst traffic quickly, then detection speed improves, but impact on device functions and performance increases
Solution Approach 1:
The patent applies local quality by deploying monitoring functions locally at distributed monitoring devices rather than centralizing all monitoring processing. Each monitoring device performs data collection and analysis locally using its own processing resources, reducing the performance burden on core network devices. This localized approach enables fast detection speed through parallel local processing while minimizing the impact on overall device performance and energy consumption.
Solution Approach 2:
The patent introduces monitoring devices as intermediary components between the network traffic and the central controller. These intermediary devices collect and pre-process traffic data, filtering and aggregating information before forwarding it to the central controller for analysis. This intermediary layer enables rapid detection by performing initial processing close to the data source while protecting core network devices from the performance impact of comprehensive monitoring operations.
3Productivity
If manual configuration is used for device management, then system complexity is reduced, but management efficiency deteriorates
Solution Approach 1:
The patent implements self-service by enabling monitoring devices to automatically generate their own configuration parameters, XPATH expressions, and subscription settings based on pre-defined templates and algorithms. The system automatically discovers network devices, determines appropriate monitoring parameters, and configures data collection without manual intervention. This automation dramatically improves management efficiency while the use of standardized templates and automated generation logic keeps system complexity manageable.
Solution Approach 2:
The patent utilizes parameter changes by dynamically adjusting monitoring parameters such as collection intervals, data types, and subscription frequencies based on network conditions and device capabilities. The system automatically modifies these parameters to optimize performance, enabling high management efficiency through adaptive automation. The complexity is controlled by limiting the range of parameter variations to pre-defined options and using algorithmic determination rather than manual configuration.
4Ease of operation
If standardized management approaches are used, then ease of operation improves, but adaptability to different device capabilities deteriorates
Solution Approach 1:
The patent applies dynamics by creating a flexible management system that can adapt its operation mode based on device capabilities. The monitoring devices dynamically adjust their data collection strategies, parameter selections, and subscription configurations according to the specific capabilities of each monitored device. This dynamic adaptation maintains ease of operation through automated decision-making while achieving high versatility in handling different device types and capabilities.
Solution Approach 2:
The patent achieves universality by designing a standardized management interface and configuration framework that can work with multiple types of network devices. The system uses universal templates and algorithms that automatically adapt to different device capabilities, allowing the same management approach to be applied across diverse devices. This universal framework maintains ease of operation while achieving broad adaptability through automated capability detection and parameter adjustment.
Data Source
AI summary
This application discloses a device management method, apparatus, system, and device, and a storage medium. The method includes: obtaining, by a first network device, an extended YANG model file from a second network device, where the extended YANG model file includes a self-explanation tag, and the self-explanation tag is used to label network operation and maintenance data; obtaining the self-explanation tag from the extended YANG model file; and managing the second network device based on the self-explanation tag. The network operation and maintenance data is labeled by using the self-explanation tag. This facilitates device management such as data collection and is not prone to errors, thereby not only achieving relatively high management accuracy, but also improving management efficiency.