5G Network Slice QoS Flow Optimization
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Solution Overview
Problem
In 5G networks, ensuring that Quality-of-Service (QoS) flows meet their service level requirements across network slices is challenging due to dynamic conditions and resource allocation inefficiencies.
Innovation Solution
The technology employs a method to create network slices in 5G networks, retrieve network information to assess QoS flow service levels, and reconfigure resource usage through network control functions to meet the required service levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If network slices are created to separate traffic for specific purposes, then service customization and QoS management are improved, but network complexity and resource allocation overhead increase
Solution Approach 1:
The patent divides the 5G network into multiple virtual network slices, each tailored for specific service requirements (e.g., enhanced mobile broadband, Internet of Things, public services). This segmentation allows independent optimization of each slice for its intended purpose while maintaining overall network functionality, directly addressing the need for service customization without requiring complete network redesign.
Solution Approach 2:
The network slice management system implements a universal framework that can handle diverse service types (mobile broadband, IoT, critical communications) through a common architecture. This multi-functional approach allows the same management infrastructure to serve multiple different service requirements, reducing overall system complexity while maintaining adaptability.
2Adaptability or versatility
If network slices are created to separate traffic for specific purposes, then service customization and QoS management are improved, but resource allocation overhead increases
Solution Approach 1:
The patent merges the management of multiple network slices into a unified management system that shares common resources and control functions. By combining slice management, resource allocation, and QoS enforcement into an integrated framework, the system reduces redundant overhead while maintaining the ability to customize resources for each specific service type.
Solution Approach 2:
The system dynamically adjusts resource allocation parameters (bandwidth, latency thresholds, priority levels) for each network slice based on real-time service requirements and network conditions. This parameter-based flexibility allows efficient resource distribution across slices without requiring dedicated fixed resources for each service, reducing overall overhead while maintaining customization.
3Reliability
If dynamic resource reconfiguration is implemented to meet QoS flow service levels, then QoS performance is improved, but control complexity and response time requirements increase
Solution Approach 1:
The patent implements a feedback mechanism where the network management system continuously monitors QoS flow performance metrics (throughput, latency, packet loss) and automatically triggers resource reconfiguration when service level agreements are violated. This closed-loop control ensures reliable QoS performance while automating the complexity of dynamic adjustments, reducing manual intervention requirements.
Solution Approach 2:
The system employs dynamic resource allocation that automatically adapts network slice configurations in response to changing QoS requirements. Control functions can modify resource parameters (bandwidth allocation, routing paths, priority settings) in real-time based on current network conditions and service demands, making the system flexible enough to handle varying QoS performance requirements without fixed rigid configurations.
4Reliability
If continuous monitoring of QoS flow service levels is performed, then service level compliance is improved, but information processing load and system overhead increase
Solution Approach 1:
The patent implements selective monitoring that focuses computational resources on critical QoS parameters and network slices with active service level violations. Rather than continuously analyzing all possible metrics across the entire network, the system applies partial monitoring actions only where and when needed, reducing information processing load while maintaining effective service level compliance detection for priority services.
Data Source
AI summary
The technology disclosed herein enables optimization of the performance of QoS flows in a network slice of a fifth-generation (5G) network. In a particular example, a method includes creating the network slices in the 5G network. The network slices comprise logically separated networks running on the 5G network. The method further includes retrieving network information indicative of whether a service level is being met for a Quality-of-Service (QOS) flow of a slice of the network slices and determining the service level for the QoS flow is not being met based on the network information. In response to determining the service level for the QoS flow is not being met, the method includes directing network control functions of the 5G network to reconfigure resource usage for the slice to achieve the service level for the QoS flow.