NWDAF Instance Selection Using Weighted Service Areas
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Solution Overview
Problem
Existing 5G core network selection procedures for NWDAF instances are inadequate when an area of interest is covered by multiple service areas, leading to inefficient data collection and prediction handling due to lack of guidance on selecting the most suitable NWDAF instance.
Innovation Solution
Assigning weights to elementary geographical areas covered by service areas of network devices hosting the same function, allowing for informed selection based on these weights to prioritize devices for data collection and prediction handling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple NWDAF instances are deployed to cover different geographical service areas, then the network can provide analytics services to multiple regions simultaneously, but it becomes difficult to select the most suitable NWDAF instance when an area of interest is covered by multiple service areas
Solution Approach 1:
The patent introduces weight parameters associated with each service area to quantify the suitability of different NWDAF instances. By changing the selection criterion from simple area overlap to weighted scoring based on these parameters, the system resolves the selection complexity while maintaining multi-region coverage capability
Solution Approach 2:
The patent implements a feedback mechanism where the NRF function receives weight information from NF functions and uses this feedback to determine the most suitable NWDAF instance. This feedback loop enables automated decision-making based on service area weights, resolving the selection difficulty
2Ease of operation
If the network uses existing selection procedures based on area overlap, then the selection process is simple, but data collection and prediction handling become inefficient when multiple NWDAF instances cover the same area
Solution Approach 1:
The patent transforms the selection process by introducing weight parameters that reflect the efficiency and suitability of each NWDAF instance for specific areas. This parameter-based approach maintains operational simplicity while dramatically improving data collection efficiency by directing requests to the most appropriate instances
3Quantity of substance
If NWDAF instances serve large service areas to maximize coverage, then fewer instances are needed, but the precision of local analytics and predictions decreases
Solution Approach 1:
The patent applies local quality by associating different weight parameters with different geographical areas within service areas. This allows each NWDAF instance to be optimized for specific local conditions, maintaining high analytics precision while enabling efficient selection through the weight-based mechanism
4Ease of operation
If the system selects any NWDAF instance that covers the area of interest, then the selection is straightforward, but seamless transitions during mobility or load balancing cannot be ensured
Solution Approach 1:
The patent implements feedback by continuously monitoring service area weights and using this information to make informed selection decisions. This feedback mechanism ensures that transitions during mobility or load balancing are smooth and reliable, as the system can dynamically determine the most suitable NWDAF instance based on current weight parameters
Data Source
AI summary
A method for delivering information relating to a first device of a communication network, the first device hosting a network function implementing at least one functionality in the network in a service area covering at least one zone that is referred to as an elementary zone. The method includes obtaining, for at least one elementary zone covered by the service area of the first device, a weight assigned to this elementary zone, the weight being a real number higher than or equal to 0; and delivering, to a second device of the network, all or some of the weights obtained.