UPF Load Balancing for 5G Network Slices

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Solution Overview

Problem

5G networks face challenges in load balancing, particularly with the User Plane Function (UPF), where certain portions of the network can become overloaded, leading to potential service disruptions and reduced performance due to increased demand from smartphones and IoT devices.

Innovation Solution

Implementing systems and methods for UPF load balancing that utilize current load thresholds, predicted throughput, and network data analytics to dynamically distribute PDU sessions across multiple UPFs, ensuring optimal resource utilization and minimizing overload by using load-regions and weighted scheduling algorithms.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If network capacity is increased to handle more smartphones and IoT devices, then bandwidth and speed are improved, but network portions can become overloaded leading to service disruptions

Engineering Contradiction:
Improvenetwork throughputVSAvoidservice continuity
Core Design Contradiction:
ProductivityVSReliability

Solution Approach 1:

The patent implements dynamic load balancing that continuously monitors UPF load metrics and adjusts session distribution in real-time. The SMF dynamically selects target UPFs based on current load conditions, transitioning from static to adaptive resource allocation to prevent overload while maintaining high throughput

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The system changes operational parameters by monitoring multiple load metrics (session count, throughput, resource utilization) and adjusting session routing decisions based on these parameter variations. This allows the network to adapt to changing traffic patterns and prevent any single UPF from becoming overloaded

Inventive Principle:
Principle #35Parameter changes

2Reliability

If load balancing is implemented across multiple UPFs, then overload is prevented and reliability is improved, but system complexity increases

Engineering Contradiction:
Improveservice continuityVSAvoidsystem architecture
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The SMF acts as an intermediary that centralizes the load balancing logic. It receives session establishment requests, evaluates UPF load conditions, and makes routing decisions, thereby simplifying the overall system architecture while achieving reliable load distribution across multiple UPFs

Inventive Principle:
Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent segments the user plane function into multiple independent UPF instances that can be distributed across different network locations. This segmentation allows parallel processing of user data while the control plane (SMF) coordinates their operation, reducing individual point of failure impact

Inventive Principle:
Principle #1Segmentation

3Measurement precision

If multiple load thresholds are maintained for each UPF and slice, then precise load control is achieved, but measurement and management complexity increases

Engineering Contradiction:
Improveload monitoring accuracyVSAvoidthreshold management
Core Design Contradiction:
Measurement precisionVSDifficulty of detecting and measuring

Solution Approach 1:

The SMF performs multiple functions including session management, UPF selection, and load balancing with a single entity. It universally handles threshold monitoring, load evaluation, and routing decisions across all slices and UPFs, reducing the need for separate management systems for each function

Inventive Principle:
Principle #6Universality (Multi-functionality)

Data Source

PatentUS20240196275A1User plane function (UPF) load balancing supporting multiple slices
Publication Date: 2024.06.13 BOOST SUBSCRIBERCO LLC
  • US20240196275A1 patent drawing
  • US20240196275A1 patent drawing
  • US20240196275A1 patent drawing

AI summary

Embodiments are directed towards systems and methods for user plane function (UPF) and network slice load balancing within a 5G network. Example embodiments include systems and methods for load balancing based on current UPF load and thresholds that depend on UPF capacity; UPF load balancing using predicted throughput of new UE on the network based on network data analytics; UPF load balancing based on special considerations for low latency traffic; UPF load balancing supporting multiple slices, maintaining several load-thresholds for each UPF and each slice depending on the UPF and network slice capacity; and UPF load balancing using predicted central processing unit (CPU) utilization and/or predicted memory utilization of new UE on the network based on network data analytics.