Dynamic Network Slice Allocation for Changing UE App Traffic
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Solution Overview
Problem
Existing network slice allocation systems in 5G networks are inefficient as they do not dynamically adjust to varying application traffic demands, leading to over-allocation of resources when applications switch between high and low bandwidth usage.
Innovation Solution
Implement a slice estimation engine on user equipment (UE) and/or the network function (UPF) to monitor and evaluate network traffic characteristics, dynamically switching network slices based on real-time application activity to optimize resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If network slice allocation is fixed for applications, then network configuration simplicity is maintained, but network resource efficiency deteriorates due to applications varying in network traffic demands over time
Solution Approach 1:
The patent implements dynamic network slice allocation where the network slice assigned to an application changes based on real-time traffic characteristics. The system monitors application traffic patterns and automatically switches between different network slices (e.g., from eMBB to URLLC or vice versa) to match current performance requirements, making the allocation flexible rather than static.
Solution Approach 2:
The system employs feedback mechanisms where traffic characteristics are continuously monitored and fed back to the slice allocation manager. This feedback loop enables the system to detect when an application's performance requirements change and trigger appropriate slice reassignment, ensuring resource efficiency while maintaining service quality.
2Loss of energy
If network slice allocation is dynamically adjusted based on real-time traffic characteristics, then network resource efficiency is improved, but system complexity increases due to continuous monitoring and switching requirements
Solution Approach 1:
The system implements self-service capabilities where the network automatically monitors its own traffic characteristics and performs self-optimization through automated slice reassignment. The slice estimation engine and monitoring infrastructure manage themselves without requiring manual intervention, reducing operational complexity while achieving resource efficiency.
Solution Approach 2:
The system changes network parameters (specifically network slice allocation) based on detected traffic characteristic changes. When traffic patterns indicate a need for different performance characteristics (e.g., switching from high bandwidth to low latency requirements), the system automatically adjusts the allocated network slice parameters to match the new requirements.
3Reliability
If applications are continuously monitored for traffic characteristics, then optimal slice selection is achieved, but processing overhead and system complexity increase
Solution Approach 1:
The system applies partial monitoring by focusing only on key traffic characteristics that indicate performance requirements changes, rather than continuously analyzing all aspects of application behavior. This selective monitoring approach achieves sufficient reliability for slice selection while reducing processing overhead to acceptable levels.
Data Source
AI summary
Systems and methods for dynamic utilization-based network slice allocation management for user equipment applications are provided. In some embodiments, a slice estimation engine may be implemented to evaluate the network traffic and other application activity data associated with an application running on the UE to determine an operating mode of the application. The slice estimation engine may trigger the UE to request an adjustment to its network slice allocation configurations based on the evaluation. To determine whether or not an application should be reconfigured for a new network slice, the slice estimation engine may evaluate processes that are running on the UE. The slice estimation engine may comprise one or more slice assessment algorithms that determine which slice from a set of available network slices would optimally serve the application based on the network traffic characteristics associated with the application's current mode of operation.