Server Configuration Templates for Hybrid 4G5G Core Deployment
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Solution Overview
Problem
Current 5G network slicing techniques face challenges in configuring underlying physical network infrastructure to meet specific user criteria, such as compute and memory resource allocation, and managing hybrid 4G/5G networks, leading to high operational costs and complexity.
Innovation Solution
The deployment of mobile network functions using dynamically generated and updated server configuration templates, which determine compute and memory resources needed for 4G/5G core deployments, allowing for hybrid support, low latency, flexible form factors, and resiliency, facilitated by AI/ML algorithms to optimize resource allocation based on Key Performance Indicators (KPIs).
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If current 5G network slicing techniques are used to configure physical network infrastructure, then network functionality is achieved, but operational costs and complexity increase significantly
Solution Approach 1:
The patent uses configuration templates that store predefined network function configurations. Instead of manually configuring each network slice from scratch, the system copies and adapts existing templates to create new configurations, significantly reducing operational complexity while maintaining flexibility.
Solution Approach 2:
The patent pre-configures network function parameters, resource allocations, and connectivity settings in templates before actual network deployment. This preliminary action allows rapid instantiation of network slices without repeated manual configuration, reducing both complexity and operational costs.
2Adaptability or versatility
If manual configuration methods are used for hybrid 4G/5G networks, then network deployment is possible, but time consumption and operational costs increase
Solution Approach 1:
The configuration templates are designed to support multiple network types (4G, 5G, and hybrid configurations) using a unified approach. A single template system handles diverse network requirements, enabling rapid deployment of hybrid 4G/5G networks without requiring separate manual configuration processes for each network type.
3Productivity
If resource allocation is optimized using AI/ML algorithms, then resource efficiency improves, but computational overhead increases
Solution Approach 1:
The system pre-calculates and stores optimal resource allocation configurations in templates based on historical data and AI/ML analysis. During actual network slicing, the system retrieves and applies these pre-computed configurations rather than performing real-time optimization, significantly reducing computational overhead while maintaining resource allocation efficiency.
Data Source
AI summary
The techniques described herein relate to methods that include: obtaining criteria for a mobile network deployment; selecting a server configuration template for a server configuration based upon the criteria; generating the server configuration for the mobile network deployment based upon the server configuration template; validating the server configuration to ensure the criteria are met by the mobile network deployment of the server configuration; deploying the server configuration as the mobile network deployment; obtaining key performance indicators from the mobile network deployment; updating the mobile network deployment in response to obtaining the key performance indicators; and updating the server configuration template in response to obtaining the key performance indicators.