Initial EAS Selection With Traffic Influence Synchronization
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Solution Overview
Problem
The existing 3GPP specifications lack clear methods for determining EAS selection and optimizing traffic routing during initial service sessions in edge computing, specifically addressing Key Issues #8 (EAS selection synchronization) and #14 (optimal user plane routing).
Innovation Solution
A method involving the Edge Enabler Client (EEC) performs EAS discovery, selects an initial EAS, and communicates with the Edge Enabler Server (EES) to trigger service session context handling and traffic influence, using messages like the Selected EAS declaration request to indicate the selected EAS and traffic influence desire, leveraging existing EDGE-3 APIs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the UE performs EAS discovery and selects an initial EAS without clear specification methods, then the service provisioning can be initiated, but the EAS selection synchronization between network functions cannot be ensured
Solution Approach 1:
The patent implements feedback mechanisms where the EES receives EAS selection information from the UE and responds with service session context handling instructions. The network functions exchange messages containing EAS endpoint information and selection criteria, ensuring synchronized updates across the system. This feedback loop resolves the contradiction by maintaining reliability through continuous information exchange while managing complexity through structured message protocols.
Solution Approach 2:
The EES acts as an intermediary between the UE and the EAS, mediating the selection process by receiving EAS discovery information from the UE, determining the appropriate EAS selection, and coordinating with the EAS. This intermediary role centralizes the synchronization logic, improving reliability while managing complexity by consolidating control in a single network function rather than distributing it across multiple entities.
2Speed
If the existing 3GPP specifications are used without additional traffic influence mechanisms, then the basic service delivery is maintained, but the optimal user plane routing cannot be achieved
Solution Approach 1:
The patent introduces traffic influence mechanisms that dynamically change routing parameters based on service session context. The EES modifies user plane routing parameters by sending traffic influence messages to the UPF, adjusting routing behavior according to EAS selection and service requirements. This resolves the contradiction by optimizing speed through dynamic parameter adjustment while managing complexity through standardized message formats and controlled intervention points in the network.
Solution Approach 2:
The system performs preliminary traffic influence configuration during the initial EAS selection phase. The EES determines and configures the optimal user plane routing before actual data traffic flows begin, based on advance knowledge of EAS location and service requirements. This preliminary action enables optimal routing speed while reducing complexity by establishing routing parameters upfront rather than dynamically adjusting them during traffic flow.
3Loss of time
If the UE autonomously selects EAS without network coordination, then the selection speed is improved, but the service session management consistency deteriorates
Solution Approach 1:
The UE performs preliminary EAS discovery and identification autonomously to reduce selection time, then submits the discovered EAS information to the EES for validation and coordination. This two-stage approach allows the UE to quickly identify potential EAS options without waiting for network responses, while the subsequent network coordination ensures service session management consistency through centralized approval and context synchronization.
Solution Approach 2:
The network functions provide feedback on the UE's autonomous EAS selection by validating the chosen EAS against service session requirements and returning confirmation or correction instructions. This feedback mechanism maintains reliability by ensuring network-wide consistency while preserving the speed benefits of autonomous UE initiation, as the UE only needs to wait for validation feedback rather than full coordination for the selection process.
Data Source
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AI summary
The embodiments herein relate to traffic influence for initial EAS selection. In some embodiments, there proposes a method (500) performed by a User Equipment (101) having a first functional component (111) implementing an enabler function. In an embodiment, the method may comprise the step of performing (S501) an Edge Application Server (EAS) discovery to discover information regarding one or more first network functions (121) implementing EASs as part of an initial service provisioning. In an embodiment, the method may further comprise the step (S502) of selecting at least one first network function (121) for implementing an initial EAS ofthe one or more first network functions (121), for providing service to a second functional component (112) implementing application function in the UE(101). In an embodiment, the method may further comprise the step of determining (S503) asecond network function (122) implementing Edge Enabler Server (EES) according to the selected at least one first network function (121) as an initial EAS. In an embodiment, the method may further comprise the step of transmitting (S504), to the determined second network function (122), amessage for triggering at least one ofservice session context handling and traffic influence. In an embodiment, the message may comprise an EAS endpoint ofthe selected initial EAS. The embodiments herein allow the service session management at the EES (that is determining which application uses which EAS service) and allow the EES to determine whether to perform traffic influence when initial EAS discovery is completed in the application layer.