EEC-EES Service Continuity Planning for UE Mobility Context Control
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Solution Overview
Problem
Existing methods for predicting user equipment (UE) mobility in edge computing systems face inefficiencies in managing application context information transmission, leading to potential resource wastage due to incorrect predictions or excessive resource usage.
Innovation Solution
A method and apparatus for controlling the transmission of prediction-based application context information through an edge enabler client (EEC) and server (EES) interaction, where the EEC transmits a registration request message with capability information, and the EES determines and responds with service continuity planning authorization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If application context information is transmitted preemptively to all neighboring edge application servers based on UE mobility prediction, then service continuity is improved, but resource waste increases due to incorrect predictions or excessive transmissions
Solution Approach 1:
The system performs preliminary actions by transmitting application context information preemptively to neighboring edge application servers before the UE actually moves to those areas. This ensures service continuity is maintained while allowing the system to rollback if predictions are incorrect, balancing reliability improvement with resource management.
Solution Approach 2:
The system implements feedback mechanisms where the source EAS receives information about whether the predicted mobility was accurate. This feedback allows the system to learn from incorrect predictions and adjust future transmissions, reducing resource waste while maintaining service continuity reliability.
2Reliability
If application context information is transmitted to all neighboring edge application servers, then service continuity is ensured, but device complexity and network overhead increase
Solution Approach 1:
Instead of uniformly transmitting context information to all neighboring EAS servers, the system applies local quality by selectively transmitting only to relevant neighboring servers based on predicted UE mobility patterns. This reduces network overhead and device complexity while maintaining service continuity where it is actually needed.
Solution Approach 2:
The system segments the set of neighboring edge application servers into relevant and irrelevant groups based on mobility predictions. Context information is transmitted only to the segmented relevant subset, reducing overall network overhead and complexity while ensuring service continuity for predicted UE locations.
Data Source
AI summary
A method performed by a first entity corresponding to an edge enabler client (EEC) in an edge computing system is provided. The method includes transmitting, to a second entity corresponding to an edge enabler server (EES), a registration request message; and receiving, from the second entity, a registration response message, wherein the registration request message includes capability information to perform service continuity planning, and wherein the registration response message includes information on allowing the service continuity planning of the first entity.


