Self-Compressed YANG Model for Lower Bandwidth Network Management
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Solution Overview
Problem
The YANG model, used for network configuration and management, is inefficient due to its human-readable text format, leading to high network bandwidth usage and processor overhead, especially in high-end network devices, which limits its deployment in applications like telemetry that require frequent monitoring.
Innovation Solution
A self-compressed YANG model that allows dynamic selection between text and compressed formats, using binary data types to store compressed data within the same model, reducing data volume by up to 85% and improving management performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If YANG model uses text format for data transmission, then human readability and compatibility are maintained, but network bandwidth consumption increases and processor overhead increases
Solution Approach 1:
The YANG model data is segmented into two representation formats: text format for human readability and compressed binary format for efficient transmission. The system selectively uses appropriate formats based on operational context, allowing both human operators and automated systems to access data in optimal formats without compromising either readability or efficiency
Solution Approach 2:
The system changes the parameter of data representation from fixed text format to a dynamic parameter that can switch between text and compressed binary formats. This parameter change is controlled based on data size thresholds and operational requirements, enabling the system to optimize between readability and transmission efficiency on demand
2Adaptability or versatility
If YANG model uses text format for data transmission, then compatibility with existing systems is maintained, but processor capability consumption increases
Solution Approach 1:
The processing system is segmented into components that handle different data formats. A compatibility layer maintains support for traditional text-based YANG models while a new compression module handles binary compressed data. This segmentation allows existing systems to continue operating with text formats while new components efficiently process compressed data, reducing overall processor burden
Solution Approach 2:
A format conversion and compression intermediary is introduced between the data source and processing systems. This intermediary automatically compresses data before transmission and decompresses when needed, shielding end systems from format complexity while maintaining compatibility. The intermediary handles the processor-intensive compression/decompression operations centrally, reducing the processor burden on distributed network elements
3Reliability
If YANG model transmits large volumes of configuration data, then complete device state monitoring is achieved, but network traffic volume increases
Solution Approach 1:
The data transmission parameter is changed from fixed text format to a dynamic format that applies compression when data volume exceeds a threshold. This parameter change maintains complete device state monitoring by transmitting all necessary data while reducing the network traffic volume through compression, achieving both reliability and efficiency
Solution Approach 2:
The system dynamically adjusts the data format based on the volume and characteristics of the configuration data being transmitted. When data volumes are small, text format is used for simplicity; when volumes exceed thresholds, compressed binary format is automatically applied. This dynamic adaptation ensures complete monitoring coverage while optimizing network traffic volume based on actual data requirements
Data Source
AI summary
Systems and methods for a self-compressed YANG (Yet Another Next Generation) model allow a model data provider (e.g., a client that provides configuration information to a server, or a server that provides response data to a query) to dynamically select either text format or compressed format using the same data model. This approach can significantly increase the YANG management performance of both network elements and servers (e.g., Operations, Administration, and Maintenance (OAM) devices). The self-compressed YANG model maintains full compatibility to existing standards/implementations, namely, the enhanced compression is available where supported.