Dynamic CU-UP Instance Spawning and Subscriber Migration
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Solution Overview
Problem
The 5G RAN architecture faces challenges in dynamically managing Centralized Unit-User Plane (CU-UP) instances to handle varying throughput requirements across peak and non-peak hours without disrupting subscriber services, and in performing seamless version upgrades or maintenance.
Innovation Solution
A method for dynamically spawning new CU-UP instances and migrating active subscribers from overloaded instances to newly created ones, allowing for efficient resource allocation and minimizing service impact, using OpenRAN and 3GPP specifications to implement CU-UP as a cloud-native network function.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If CU-UP instances are statically deployed to handle peak traffic, then throughput capability is improved, but resource utilization deteriorates during non-peak hours
Solution Approach 1:
The patent implements dynamic scaling of CU-UP instances based on real-time traffic conditions. During peak hours, additional CU-UP instances are spawned to handle increased throughput requirements. During non-peak hours, instances are terminated or migrated to reduce resource consumption. This dynamic adjustment resolves the contradiction between maintaining high throughput capability and optimizing resource utilization.
Solution Approach 2:
The system changes the operational parameters of CU-UP instances by migrating subscribers between instances with different resource allocations. During peak hours, subscribers are redistributed to instances with higher capacity. During non-peak hours, instances are consolidated to reduce resource consumption. This parameter change enables the system to adapt throughput capability to actual demand.
2Reliability
If CU-UP instances are scaled up to handle peak traffic, then service reliability is improved, but system complexity increases
Solution Approach 1:
The CU-UP function is segmented into multiple independent instances that can be scaled individually. Each instance handles a subset of subscribers and can be independently managed. This segmentation allows the system to maintain high service reliability by distributing load across multiple instances while managing complexity through standardized instance templates and automated management.
Solution Approach 2:
The patent uses copying by spawning multiple identical CU-UP instances that can be rapidly deployed. These instances are created using standardized templates, allowing quick replication during peak hours without increasing operational complexity. The copied instances are functionally equivalent and can be managed through uniform procedures.
3Ease of operation
If manual CU-UP instance management is used, then operational simplicity is maintained, but productivity deteriorates
Solution Approach 1:
The system implements self-service through automated detection and response to traffic conditions. When traffic thresholds are exceeded, the system automatically spawns new CU-UP instances and migrates subscribers without manual intervention. This maintains operational simplicity while dramatically improving deployment speed and responsiveness.
Solution Approach 2:
The patent prepares instance templates and migration procedures in advance, allowing rapid deployment of new CU-UP instances when needed. Pre-configured templates eliminate the need for manual configuration, maintaining operational simplicity while enabling fast scaling. Subscriber migration procedures are also pre-planned to ensure seamless transitions.
4Reliability
If CU-UP instances are maintained during peak hours, then service continuity is improved, but energy consumption increases
Solution Approach 1:
The system dynamically adjusts the operational state of CU-UP instances based on traffic demand. During peak hours, instances remain active to maintain service continuity. During non-peak hours, instances are terminated or put into low-power states, significantly reducing energy consumption. This dynamic state adjustment resolves the contradiction between service continuity and energy efficiency.
Data Source
AI summary
This disclosure provides dynamic spawning of CU-UP instances and migration of some of active subscribers from overloaded CU-UP instance to newly created CU-UP instance without service disruption. In one embodiment, a method of migrating an active subscriber from a first Centralized Unit-User Plane (CU-UP) instance to a newly provided second CU-UP instance includes determining a first CU-UP requires service; spawning the second CU-UP instance; and migrating a subscriber from the first CU-UP instance to the second CU-UP instance.