VM Resource Scheduling Policy Adjustments for QoS and Energy Efficiency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The existing resource management methods for virtual machine systems in cloud computing environments face challenges in ensuring Quality of Service (QoS) due to independent physical resource scheduling on the physical device platform, which can lead to delays in virtual machine creation and energy inefficiencies from repeated power-ups and power-downs.
Innovation Solution
A resource management method that adjusts physical resources scheduling policies based on QoS constraint parameters and current operating status indicators of virtual machine clusters, suppressing unnecessary power-downs and power-ups, and optimizing resource allocation to ensure timely and efficient virtual machine creation and updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If independent physical resource scheduling is performed on the physical device platform to reduce energy consumption, then energy efficiency is improved, but virtual machine creation and update delays occur
Solution Approach 1:
The patent applies preliminary action by having the virtual resource management platform predict future virtual machine creation and update requirements based on historical data and current trends. This allows the system to proactively maintain physical machines in an active state before actual scheduling decisions are made, preventing delays while still allowing energy-saving scheduling when predictions indicate no imminent resource needs.
2Loss of energy
If physical machines are powered down to save energy when utilization is low, then energy consumption is reduced, but repeated power-up and power-down operations occur
Solution Approach 1:
The patent implements feedback mechanisms where the virtual resource management platform continuously monitors physical machine states, virtual machine workload patterns, and scheduling decisions. This feedback loop allows the system to learn from past power-up/power-down cycles and improve predictions, reducing unnecessary power transitions while maintaining energy efficiency through optimized scheduling based on actual resource utilization patterns.
Data Source
AI summary
An embodiment of the present invention provides a resource management method for a virtual machine system, where the method includes: obtaining, by a virtual resource management platform, a QoS constraint parameter of a virtual machine cluster and a current operating status statistical indicator of the virtual machine cluster, and according to the QoS constraint parameter of the virtual machine cluster and the current operating status statistical indicator of the virtual machine cluster, adjusting physical resources scheduling policy of a physical device platform or performing physical resource scheduling on the physical device platform. The method may ensure QoS of a cloud application.