Mobile Edge Application Relocation Timing
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Solution Overview
Problem
Current mobile edge computing systems face significant latency issues during application relocation between mobile edge servers due to user mobility and load balancing, which can negatively impact user experience.
Innovation Solution
A method is introduced to facilitate the relocation of mobile edge applications from a source server to a target server based on control data indicative of user engagement, such as computational load and sensor data, to minimize the impact on the user experience by synchronizing relocation with periods of reduced user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If application relocation is performed between ME servers, then adaptability to user mobility and load balancing is improved, but latency increases and user experience deteriorates
Solution Approach 1:
The system performs preliminary actions by monitoring user engagement metrics and identifying optimal relocation moments before actual relocation occurs. The source ME server or ME control node continuously assesses user engagement levels and prepares relocation opportunities in advance, executing the relocation at the most favorable moment rather than reactively when mobility events occur.
Solution Approach 2:
The system dynamically adjusts relocation decisions based on real-time user engagement conditions. Instead of following a static relocation policy, the system continuously monitors control data indicating user engagement and adapts the relocation timing and execution based on current system state, making the relocation process flexible and condition-dependent.
2Productivity
If application relocation is performed between ME servers, then load balancing capability is improved, but user experience deteriorates due to perceived latency and glitches
Solution Approach 1:
The system implements feedback mechanisms by monitoring control data that indicates user engagement levels during application execution. This feedback information is used to adjust relocation decisions, allowing the system to balance load across ME servers while maintaining user experience quality. The feedback loop enables the system to recognize when relocation should be deferred to maintain reliability.
Solution Approach 2:
The system changes operational parameters by considering user engagement metrics as a key factor in relocation decisions. Instead of relying solely on traditional parameters like load distribution and geographic location, the system incorporates user engagement state as a dynamic parameter that influences relocation timing, thereby maintaining service quality during load balancing operations.
3Adaptability or versatility
If application relocation is initiated by source ME server, then relocation flexibility is improved, but system complexity increases due to coordination requirements
Solution Approach 1:
The source ME server performs self-service by autonomously monitoring user engagement metrics and making relocation decisions without requiring complex external coordination. The server independently assesses whether relocation conditions are met and executes relocation when appropriate, reducing the coordination burden on other system components while maintaining flexibility.
Data Source
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AI summary
Based on control data (1002) indicative of a user engagement in a mobile edge application (1001) which is being executed on a source mobile edge server (201-203) of a mobile edge system (200) and on a terminal (130), relocation of the mobile edge application (1001) from the source mobile edge server (201-203) to a target mobile edge server (201-203) is facilitated.