MEC Virtual Machine Allocation for Seamless UE Handover
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Solution Overview
Problem
In mobile edge computing, resource wastage occurs due to prediction errors during user equipment (UE) handovers, leading to inefficient use of virtual machines and deteriorated user experience, especially when multiple users access the same MEC server.
Innovation Solution
Implementing a mobile edge computing method where a management network element creates a new virtual machine on an MEC server based on a virtualization resource request from the target RAN, ensuring seamless handover without affecting service continuity, and sends the necessary information to the control plane to manage resource allocation and data migration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cloud-based prediction of user location is used to preconfigure VMs, then service continuity is maintained during handover, but prediction errors cause redundant VM creation and resource waste
Solution Approach 1:
The patent applies preliminary action by pre-establishing VM migration mechanisms and resource allocation frameworks before handover occurs. The system prepares VM migration capabilities and resource pools in advance, enabling rapid VM relocation when handover happens, thus maintaining service continuity without relying on inaccurate location predictions.
Solution Approach 2:
The patent implements feedback mechanisms where the MEC management network element continuously monitors actual user location, handover events, and VM performance. This feedback loop allows the system to learn from prediction errors and optimize future VM allocation decisions, reducing redundant VM creation while maintaining service continuity.
2Reliability
If redundant virtual machines are created due to prediction errors, then service continuity is ensured, but resource utilization deteriorates and user experience worsens
Solution Approach 1:
The patent changes key parameters including VM lifecycle management parameters, resource allocation parameters, and handover detection parameters. By dynamically adjusting these parameters based on actual handover events and resource availability, the system optimizes resource utilization while ensuring service continuity during UE handover.
Solution Approach 2:
The patent introduces dynamic VM allocation and migration capabilities where VMs can be dynamically created, migrated, or terminated based on real-time handover events and resource conditions. This dynamic approach replaces static prediction-based allocation, improving both service continuity and resource utilization efficiency.
3Reliability
If VMs are preconfigured based on location prediction, then handover service is maintained, but transmission latency increases due to redundant processing
Solution Approach 1:
The patent enables rapid VM migration by skipping unnecessary prediction and verification steps. When handover is detected, the system directly migrates the VM to the target MEC server using pre-established resource pools and migration mechanisms, thus reducing transmission latency while maintaining handover service continuity.
Data Source
AI summary
A mobile edge computing method and apparatus are provided. The method which is implemented by a mobile edge computing (MEC) management network element includes: receiving an MEC virtualization resource request sent by a control plane of a target radio access network (RAN), wherein the control plane belongs to the target RAN to which user equipment (UE) is handed over, and the MEC virtualization resource request includes an MEC computing resource requirement of the UE; creating, based on the MEC virtualization resource request, a new virtual machine (VM) on an MEC server for the UE, wherein the new VM is used on the target RAN side after the handover; and sending first information of the new VM to the control plane, wherein the first information includes an ID of the new VM. According to the application, the efficiency of usage of resources during a handover of UE is significantly improved.