Visited NRF Caching for 5G PLMN Service Latency Reduction
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Solution Overview
Problem
In 5G telecommunications networks, the routing of requests for Nnrf service operations from a visited network to a home network and vice versa increases latency due to the need for each request and response to traverse between public land mobile networks (PLMNs), consuming significant network bandwidth and resources.
Innovation Solution
Implementing a method where the visited Network Function Repository Function (NRF) identifies and processes locally requests that can be handled without forwarding them to the home NRF, caching information from initial responses to handle subsequent requests efficiently, and using NFStatusSubscribe to maintain updated NF profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If requests for Nnrf service operations are routed from visited network NRF to home network NRF, then service accuracy and data consistency are improved, but service latency increases and network bandwidth is consumed
Solution Approach 1:
The visited NRF proactively subscribes to NF profile updates from the home NRF using NFStatusSubscribe before actual service requests occur. This preliminary action caches NF profile data locally, so when service requests arrive, the visited NRF can immediately serve them from cached data without forwarding to the home NRF, thus reducing latency while maintaining data consistency through pre-established subscriptions.
Solution Approach 2:
The visited NRF acts as an intermediary between consumer NFs and the home NRF. Instead of consumer NFs directly communicating with the home NRF, the visited NRF receives subscriptions, caches NF profile data locally, and serves requests from its local cache. This intermediary role eliminates the need for each request to traverse to the home network, reducing latency while the subscription mechanism ensures data consistency is maintained.
2Reliability
If requests for Nnrf service operations are routed from visited network NRF to home network NRF, then data consistency across PLMNs is improved, but network bandwidth and resources are consumed
Solution Approach 1:
The visited NRF performs preliminary actions by subscribing to NF profile update notifications from the home NRF using the NFStatusSubscribe service operation. This subscription establishes a push mechanism where the home NRF sends updates only when changes occur, rather than the visited NRF continuously polling or forwarding all requests. This approach maintains data consistency while minimizing network bandwidth consumption by transmitting data only when necessary.
Solution Approach 2:
The visited NRF creates local copies (caches) of NF profile data received from the home NRF. Instead of maintaining direct real-time connections for every service operation, the visited NRF stores copies of NF profiles locally and serves requests from these copies. This copying mechanism maintains data consistency for the duration of the cache validity while dramatically reducing network bandwidth consumption by eliminating repeated traversals to the home network.
3Loss of time
If the visited NRF processes all inter-PLMN requests locally using cached data, then service latency is reduced, but data accuracy may deteriorate
Solution Approach 1:
The visited NRF implements a feedback mechanism by subscribing to NFStatusSubscribe notifications from the home NRF. This subscription creates a feedback loop where the home NRF notifies the visited NRF of any changes to NF profiles. When updates occur, the visited NRF receives notifications and updates its local cache accordingly, ensuring data accuracy is maintained despite using cached data for local processing. The feedback mechanism triggers cache invalidation and refresh only when necessary.
Solution Approach 2:
The visited NRF dynamically manages its local cache of NF profile data, transitioning between states of cached data usage and home NRF consultation. The system adapts its behavior based on cache validity status: when cache is valid, it processes requests locally for low latency; when cache becomes stale (detected through subscription feedback), it updates from the home NRF. This dynamic approach optimizes the trade-off between latency and data accuracy in real-time.
Data Source
AI summary
A method for reducing inter-PLMN forwarding of messages relating to Nnrf service operations includes receiving, at a first NRF, a first request for an Nnrf service operation, determining that the first request identifies a PLMN different from a PLMN of the first NRF, determining that the first request cannot be processed locally at the first NRF, and, in response, forwarding the first request to a second NRF in the PLMN identified in the first request. The method further includes receiving, from the second NRF, a response to the first request, caching information from the response, receiving a second request for an Nnrf service operation, determining that the second request identifies a PLMN different from the PLMN of the first NRF, determining that the second request can be processed locally at the first NRF, and processing the second request locally at the first NRF using the cached information from the first response.