VM Migration via Power Prediction
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Solution Overview
Problem
Conventional virtual machine migration approaches do not consider the power utilization of target host devices, leading to potential performance issues and remigration challenges due to insufficient power.
Innovation Solution
A migration management platform that predicts and forecasts the power requirements of virtual machines and host devices, allowing for intelligent migration decisions based on available power and resource imbalances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If virtual machine migration is performed without considering power utilization, then migration speed and simplicity are improved, but system reliability and performance stability deteriorate due to potential power insufficiency on target host devices
Solution Approach 1:
The system performs preliminary power utilization analysis and prediction before executing virtual machine migration. Power utilization data is retrieved and analyzed in advance, and the target host device is selected based on predicted power requirements, ensuring power sufficiency before migration occurs.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring power utilization data of host devices and using this information to make informed migration decisions. The power utilization feedback loop ensures that migration decisions are based on current and predicted power states of target devices.
2Reliability
If power utilization analysis is performed for each virtual machine migration, then system reliability is improved, but computational complexity and processing time increase
Solution Approach 1:
The system employs a universal power utilization analysis framework that can be applied to any virtual machine migration scenario. The power analysis engine serves multiple functions including retrieving power data, predicting power requirements, and selecting target devices, making the system adaptable to different migration contexts without requiring separate analysis mechanisms.
3Stability of the object's composition
If power utilization data is retrieved and analyzed for target device selection, then performance stability is improved, but energy consumption and processing overhead increase
Solution Approach 1:
The system performs partial power utilization analysis by focusing on critical power metrics and predictions necessary for migration decisions, rather than analyzing all possible system parameters. This selective approach ensures sufficient performance stability while minimizing unnecessary energy consumption and processing overhead.
Data Source
AI summary
A method comprises retrieving power utilization data of a plurality of host devices and identifying at least one virtual machine for migration from a source host device to a target host device of the plurality of host devices. In the method, power utilization of the at least one virtual machine is predicted. The target host device is determined based, at least in part, on the power utilization data of the plurality of host devices and the predicted power utilization of the at least one virtual machine. The method further comprises migrating at least one virtual machine from the source host device to the target host device.