Dynamic User Plane Node Selection in CUPS Networks
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Solution Overview
Problem
Current methods for selecting user plane nodes in mobile networks, such as those in 3GPP and 5G architectures, rely on static criteria and do not effectively utilize dynamic information, leading to suboptimal performance in terms of latency and load distribution.
Innovation Solution
A method that involves storing static and dynamic information about user plane nodes, calculating dynamic scores based on received information, and dynamically selecting the preferred node for user sessions, taking into account factors like service capabilities, latency, and hardware acceleration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If static selection criteria are used for user plane node selection, then the selection process is simple and fast, but the performance in terms of latency and load distribution is suboptimal
Solution Approach 1:
The patent implements dynamic selection of user plane nodes by introducing a selection module that periodically receives dynamic information (load status, latency, service capabilities) from user plane nodes and calculates dynamic scores. This transforms the static selection mechanism into a dynamic one that adapts to changing network conditions, thereby improving load distribution and performance while managing complexity through structured information collection and scoring.
Solution Approach 2:
The selection module establishes a feedback loop by periodically receiving dynamic information from user plane nodes about their current status, using this information to calculate updated dynamic scores, and selecting nodes based on these scores. This feedback mechanism enables the system to continuously optimize load distribution based on real-time network conditions while maintaining a systematic approach to managing the increased complexity.
2Loss of time
If dynamic information is collected and used for node selection, then latency is reduced and user experience is improved, but the system complexity increases
Solution Approach 1:
The selection module periodically receives and stores dynamic information from user plane nodes in advance of actual selection needs. By maintaining an updated database of dynamic information (load status, latency, service capabilities) before selections are required, the system reduces latency during actual selection operations while the periodic information collection manages the complexity burden over time.
Solution Approach 2:
The system changes from using only static parameters for node selection to using dynamic parameters (load status, latency measurements, service capabilities) that change over time. This parameter transformation enables reduced latency and improved user experience by selecting nodes based on current conditions, while the structured approach to collecting and processing these parameters manages the associated complexity.
3Productivity
If dynamic scoring and selection is implemented, then optimal load distribution is achieved, but the processing overhead increases
Solution Approach 1:
The selection module implements dynamic scoring and selection periodically rather than continuously, and only for user plane nodes that are candidates for selection. This partial action approach achieves optimal load distribution through dynamic scoring while reducing processing overhead by limiting the scope and frequency of dynamic evaluations to only when necessary for selection decisions.
Data Source
AI summary
In some embodiments, a selection module associated with a control plane node implementing CUPS functionality can identify a user plane element for assigning user plane functionalities based on static and/or dynamic selection criteria. Dynamic criteria can include, for example, load information, latency, and hardware acceleration support. In some embodiments, a control plane node can determine whether to implement a CUPS or a non-CUPS session. If a non-CUPS session is determined, the CUPS control plane node can assume user plane functionalities in addition to control plane functionalities.