Network Function Selection Using Dynamic Capacity Ranking
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Solution Overview
Problem
Existing network function selection methods in 5G telecommunications networks rely on static priority information, which is less effective for dynamic load balancing and can lead to inefficient resource utilization and increased latency.
Innovation Solution
Implement a network function discovery node that calculates dynamic priority based on available capacity using a rank processing algorithm, considering permissible and abatement load thresholds to optimize network function selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If static priority information is used for network function selection, then the selection process is simple and deterministic, but load balancing effectiveness deteriorates and resource utilization becomes inefficient
Solution Approach 1:
The patent transforms static priority information into dynamic priority values that change over time based on network conditions. The priority of network functions is continuously updated according to their current load states, allowing the selection process to adapt to changing network conditions while maintaining computational efficiency through the discovery node's processing capabilities.
Solution Approach 2:
The patent changes the parameter of priority from a fixed static value to a dynamic value that varies based on network function load states. By continuously monitoring and updating priority values according to current network conditions, the system achieves effective load balancing while the discovery node manages the computational complexity of these dynamic parameter changes.
2Ease of manufacture
If static priority information is used for network function selection, then implementation is straightforward, but resource utilization efficiency deteriorates
Solution Approach 1:
The patent introduces a feedback mechanism where network functions periodically report their current load states to the discovery node. This feedback loop enables the discovery node to update priority values based on actual resource consumption patterns, thereby improving resource utilization efficiency while the structured feedback protocol maintains implementation clarity.
Solution Approach 2:
The patent enables network functions to self-report their own load states and capacity information to the discovery node. This self-service approach allows the system to automatically adjust priorities based on actual resource usage without requiring external intervention, improving resource utilization efficiency while keeping the implementation process organized and manageable.
3Stability of the object's composition
If static priority information is used for network function selection, then the system is stable and predictable, but latency increases due to inefficient resource allocation
Solution Approach 1:
The patent introduces dynamic priority updates that respond to changing network conditions, allowing the system to adapt to varying loads and reduce latency. The discovery node processes these dynamic changes efficiently, maintaining predictability through structured update mechanisms while reducing the time lost to inefficient resource allocation decisions.
Solution Approach 2:
The patent implements preliminary actions by having network functions periodically report their status in advance, allowing the discovery node to prepare priority updates before they are needed. This proactive approach reduces latency by ensuring that priority information is already optimized when selection decisions are made, while maintaining system stability through scheduled updates.
4Productivity
If dynamic priority based on available capacity is implemented, then load balancing improves and latency decreases, but processing complexity increases
Solution Approach 1:
The patent introduces a discovery node as an intermediary component that centralizes the complex calculations for determining available capacity and updating priorities. This intermediary structure allows the rest of the network to remain simple while the discovery node handles the computational complexity of processing load states and capacity information from multiple network functions.
Solution Approach 2:
The patent segments the network into producer network functions that report their status and consumer network functions that make selection decisions. The discovery node acts as a separate processing entity that handles the complex calculations, dividing the overall system complexity into manageable segments that can be processed independently and efficiently.
Data Source
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AI summary
Methods, systems, and computer readable media for rank processing in network function selection. A method includes periodically receiving, at a network function discovery node, and from each producer network function of a number of producer network functions, a current load value specifying a computing load carried by the producer network function. The network function discovery node is configured for performing service discovery between network functions of a telecommunications core network. The method includes determining, for each producer network function, an available capacity for the producer network function based on the current load value and a published capacity of the producer network function. The method includes responding to a network function discovery request from a consumer network function using the available capacity of each producer network function.