5G Distributed Data Mesh for Low-Latency Network Data Access
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Solution Overview
Problem
Mobile networks face challenges in managing vast amounts of data generated across network infrastructure components, leading to data loss, increased complexity, and resource expenditure due to the use of data lakes, which cause issues with data access, redundancy, and architecture sprawl, especially exacerbated by 5G networks.
Innovation Solution
A distributed data mesh system is implemented to manage and organize data by identifying data domains, using data pools to store data close to its source, preventing data movement, and employing a data catalog to ensure data accessibility and compliance with predefined standards, thereby minimizing latency and resource waste.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data lakes are used to store and manage network data, then data storage capacity is improved, but data access efficiency deteriorates and architecture complexity increases
Solution Approach 1:
The patent segments the monolithic data lake into multiple specialized data pools organized by data domain (e.g., RAN domain, core network domain, subscriber domain). Each data pool stores specific types of data and can be independently accessed, eliminating the need to search through entire data lakes and improving data access efficiency while maintaining storage capacity.
Solution Approach 2:
The patent introduces a data mesh layer as an intermediary between data sources and data consumers. This mesh includes data domains, data pools, and data products that mediate data access requests, enabling efficient retrieval without direct access to the underlying storage infrastructure, thus improving ease of operation.
2Ease of operation
If data is moved across the network for centralized processing, then data accessibility is improved, but network latency increases and resources are wasted
Solution Approach 1:
The patent implements local quality by allowing data to remain stored in its source domain's data pool while providing remote access capabilities. Data products can be accessed by computing devices in different domains without physically moving the data, reducing latency and resource consumption while maintaining accessibility.
Solution Approach 2:
The patent creates virtual copies or references to data through data products rather than physically copying or moving data. Computing devices can access data products that reference the original data location, enabling efficient access without data movement, thus reducing network latency and resource waste.
3Adaptability or versatility
If data is stored in multiple data pools across different domains, then data organization is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal data mesh architecture that provides consistent data access mechanisms across all data domains. The same data product interface and access protocols work across different domains (RAN, core network, subscriber), simplifying the system despite the distributed nature of data pools by providing a unified view and access method.
Data Source
AI summary
A distributed data mesh system for networks is described herein. The distributed data mesh system includes data organized into separate domains, where each domain includes one or more data products representing the data in the domain. The distributed data mesh system additionally includes a data infrastructure catalog that includes information describing the data products and data domains. The distributed data mesh system is also designed based on a set of governing principles which govern how data is created, used, and maintained.