Edge Computing Service Migration System for Mobile User Optimization
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Solution Overview
Problem
Existing service migration methods in multi-access edge computing environments are inefficient when handling multiple mobile users, as they consider individual terminal movements, leading to excessive resource consumption and delay due to frequent service interruptions.
Innovation Solution
A migration system that collects location and resource data to determine the necessity of migration based on service delay time, service interruption time, and operation cost, using a migration necessity score calculation and comparison to optimize migration decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If service migration is performed frequently to maintain service access performance for mobile terminals, then service quality is improved, but resource consumption increases and service interruption delay increases
Solution Approach 1:
The patent merges the migration decisions of multiple terminals into a single aggregated decision. Instead of evaluating each terminal's mobility independently, the system combines mobility patterns of multiple terminals using the same virtualization service and performs migration at aggregated time points, reducing the frequency of service interruptions while maintaining service quality.
Solution Approach 2:
The system performs preliminary evaluation of migration necessity by collecting location data and calculating migration scores before actual migration occurs. This allows the system to plan migrations in advance based on predicted mobility patterns, reducing reactive service interruptions and improving service access performance.
2Reliability
If service migration is performed for each individual terminal movement, then service access performance is maintained, but edge cloud server resources are consumed inefficiently
Solution Approach 1:
The patent combines migration evaluations for multiple terminals into a single aggregated decision process. By merging individual terminal mobility data into collective migration scores, the system reduces the number of separate migration operations, thereby decreasing edge cloud server resource consumption while maintaining service performance.
Solution Approach 2:
The system creates a universal migration evaluation mechanism that serves multiple terminals simultaneously. The migration necessity score calculation and comparison units evaluate the collective state of multiple terminals, enabling a single migration decision to benefit multiple users, thus improving resource efficiency.
3Productivity
If comprehensive migration evaluation considering multiple terminals is performed, then resource efficiency is improved, but system complexity increases
Solution Approach 1:
The patent segments the complex migration evaluation process into distinct functional modules: location data collection, resource data collection, migration necessity score calculation, score comparison, and migration execution. This modular segmentation manages system complexity by organizing the comprehensive multi-terminal evaluation into manageable, independent components.
Solution Approach 2:
The migration necessity score acts as an intermediary metric that simplifies the complex evaluation of multiple terminals' mobility patterns and resource states. By converting diverse input data into a single comparable score, the system manages complexity while maintaining comprehensive evaluation capabilities.
Data Source
AI summary
The present disclosure relates to a service migration system in an edge computing environment. Provided is a migration system comprising: a position data collection unit for collecting position data of each user terminal; a resource data collection module for collecting resource data of each edge cloud server connected to each user terminal; and a migration module for determining the necessity of migration, and performing migration, wherein the necessity of migration is determined on the basis of the service delay time, the service interruption time, and the operation costs.