Service Migration Module for Seamless Wireless Handover
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Solution Overview
Problem
Existing wireless communication systems face challenges in efficiently migrating services between base stations due to large data volumes, leading to performance degradation, especially for real-time applications like augmented reality and online gaming, as existing protocols like CXTP are not suitable for server migrations which require significant resources and time.
Innovation Solution
A migration managing module that determines the optimal time for service migration based on resource requirements, estimates the impact on service quality, and selects a target server by evaluating probability values, cost, and resource availability, thereby minimizing service interruption during handovers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the server is migrated from one base station to another, then the service can follow the user equipment movement, but the large volume of data transfer causes migration time to increase
Solution Approach 1:
The system performs preliminary actions by predicting future handover events and initiating service migration before the actual handover occurs. The migration managing module determines prediction time points based on mobility patterns and triggers migration in advance, allowing data transfer to start early and reducing the impact on service continuity during actual handover.
Solution Approach 2:
The system dynamically adjusts migration timing and target selection based on real-time conditions. The migration managing module continuously monitors user equipment mobility, network state, and service requirements to adaptively determine when and where to migrate services, optimizing the balance between service continuity and migration time.
2Speed
If the server migration is performed frequently to track user equipment, then service responsiveness is improved, but the resource consumption and complexity increase
Solution Approach 1:
The system implements feedback mechanisms where the migration managing module continuously monitors user equipment mobility patterns, network conditions, and service performance. Based on this feedback, the system intelligently determines whether migration is necessary, adjusting migration frequency to match actual service needs rather than following every handover event, thus reducing unnecessary complexity.
Solution Approach 2:
The system changes key parameters such as migration trigger thresholds, prediction time points, and target selection criteria based on service requirements and network conditions. By dynamically adjusting these parameters, the system optimizes service responsiveness while avoiding excessive migration operations that would increase complexity.
3Use of energy by moving object
If the service migration is delayed to reduce data transfer volume, then resource usage is optimized, but service interruption time increases
Solution Approach 1:
The system performs data transfer in advance during prediction time points before actual handover occurs. This preliminary action allows the migration to be staged and prepared early, so that when the actual handover happens, the service can be switched with minimal interruption, effectively resolving the trade-off between transfer efficiency and interruption time.
Data Source
AI summary
A method and a migration managing module for managing a migration of a service. The migration managing module determines a point in time relating to completion of the migration of the service based on resource requirements related to the service. For each radio network node a respective impact on a quality of the service is estimated. Moreover, the migration managing module selects from among servers at least one respective target server for which the respective server location measure of said at least one respective target server matches the respective radio network node location measure of said each radio network node, thereby obtaining a set of target servers comprising said at least one respective target server for said each radio network node. For each target server, a respective cost of the migration based on the resource requirements related to the service is determined. A respective tendency as a function of said each probability value, the respective cost and the respective impact is determined. A target server of the set of target servers based on tendencies is selected. The migration of the service from the source server to the target server is performed. A computer program and a carrier therefor are also disclosed.