Virtual Machine Migration Trigger Method for Cloud Server Load Reduction
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Solution Overview
Problem
Existing server systems face inefficiencies due to frequent execution of virtual machine migration computational procedures, leading to excessive resource occupation and reduced user experience, as they attempt to optimize server performance by periodically migrating virtual machines based on various factors.
Innovation Solution
A trigger method for virtual machine migration that utilizes a cloud server to receive connection data from client end hosts, determining when to initiate the migration procedure based on specific thresholds, thereby reducing unnecessary computations and optimizing server resource usage by executing the procedure only when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the computational procedure is executed periodically with high frequency to optimize virtual machine migration, then the server performance optimization is improved, but the server resource occupation increases excessively
Solution Approach 1:
The patent implements dynamic execution frequency adjustment by monitoring server load metrics (CPU usage, memory usage, temperature) and adapting the computational procedure execution frequency accordingly. When server load is low, migrations occur more frequently to optimize performance; when load is high, frequency decreases to preserve user resources, resolving the contradiction between optimization and resource availability
Solution Approach 2:
The system changes the parameter of execution frequency based on real-time server conditions. By dynamically adjusting the time interval between computational procedure executions according to server load parameters, the system achieves both performance optimization and resource preservation without fixed periodic execution
2Reliability
If the computational procedure is executed frequently to maintain optimal virtual machine distribution, then the connection quality is improved, but the computation load and system resource occupation increase
Solution Approach 1:
The patent implements conditional periodic action where computational procedures execute at intervals determined by server load conditions rather than fixed periodic schedules. The system monitors metrics and adjusts migration timing dynamically, achieving connection quality maintenance while reducing unnecessary computation during low-load periods
Solution Approach 2:
The system employs feedback mechanisms by continuously monitoring server performance metrics (CPU, memory, temperature) and using this information to determine when migration computations are necessary. This feedback loop prevents unnecessary executions during stable conditions, reducing system resource occupation while maintaining connection quality when needed
3Productivity
If the computational procedure is executed with low frequency to reduce resource occupation, then the server resource availability is improved, but the connection quality may deteriorate
Solution Approach 1:
The system dynamically adjusts migration frequency based on real-time server conditions and connection quality metrics. When connection quality degrades or server load increases, the system increases migration frequency to restore optimal performance, while maintaining low frequency during stable conditions to preserve resource availability
Data Source
AI summary
A method of triggering a computational procedure for virtual machine migration includes receiving by a cloud server, reply connection data from a client end host, and determining if the computational procedure for virtual machine migration is initiated according to the reply connection data. The virtual machine migration is performed upon completion of the computational procedure. A browser intercepts the reply connection data to reply to the cloud server when the client end host accesses a web page via the browser. The reply connection data from the client end host is used for determining whether the computational procedure is initiated or not so as to lower a cloud server computation load by reducing the computational procedures performed.