Edge Enabler Server Target Selection for Service Continuity
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Solution Overview
Problem
In densely deployed edge computing environments, selecting the optimal target Edge Application Server (EAS) for service continuity is challenging due to multiple available servers, and existing methods do not adequately consider user and application preferences and performance requirements (KPIs).
Innovation Solution
A method where the Edge Enabler Client (EEC) in the User Equipment (UE) sends selection criteria to the source Edge Enabler Server (EES) to determine the need for application context transfer and select the target EAS based on user and application preferences and KPIs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple edge servers are deployed to provide service continuity, then service reliability is improved, but server selection complexity increases
Solution Approach 1:
The patent introduces an Edge Enabler Server (EES) as an intermediary that centralizes the server selection process. The EES receives selection criteria from the UE, determines application context transfer needs, and selects the target EAS based on predefined criteria such as distance, load, and user preferences. This mediator approach resolves the contradiction by handling selection complexity centrally while maintaining service continuity across multiple servers.
2Ease of operation
If automated server selection is implemented, then ease of operation is improved, but system complexity increases
Solution Approach 1:
The patent implements preliminary action by having the UE provide selection criteria to the EES in advance, before the actual server selection is needed. The EES stores these criteria and uses them automatically when server selection is required, eliminating the need for real-time complex decision-making. This approach automates the selection process while managing system complexity through pre-configured parameters.
3Reliability
If selection criteria based on user preferences and KPIs are implemented, then service quality is improved, but information processing requirements increase
Solution Approach 1:
The patent transforms complex user preferences and application requirements into standardized selection criteria parameters that the EES can process efficiently. These parameters include distance thresholds, load conditions, and user-defined preferences, which are structured in a format that minimizes information processing requirements while maintaining service quality. The EES evaluates these parameters systematically to select the optimal target server.
Data Source
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AI summary
The present disclosure relates to a communication method and system for converging a 5th-Generation (5G) communication system for supporting higher data rates beyond a 4th-Generation (4G) system with a technology for Internet of Things (IoT). The present disclosure may be applied to intelligent services based on the 5G communication technology and the loT-related technology, such as smart home, smart building, smart city, smart car, connected car, health care, digital education, smart retail, security and safety services. A method performed by a source edge enabler server for selecting a target edge application server in an edge computing system for a user equipment (UE) is provided. The method includes receiving, from an edge enabler client in the UE, a selection criteria for selecting the target edge application server; determining a need for an application context transfer for an application client in the UE; selecting the target edge application server for the application context transfer based on the selection criteria received from the edge enabler client; and transmitting, to the edge enabler client, a notification about the selected target edge application server.