Hypervisor Dynamic Resource Reallocation for Underutilized Virtual Machines
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In virtualization environments, hardware resources are often overcommitted to virtual machines (VMs), and legacy VMs continue to consume resources even though they are underutilized, leading to inefficient resource allocation and the need for manual auditing, which is laborious and often results in VM migration rather than optimal resource reallocation.
Innovation Solution
A method where a hypervisor monitors the usage of hardware resources by VMs and automatically decreases the assigned resources when usage falls below a threshold, allowing for dynamic reallocation without shutting down or migrating VMs, thereby optimizing resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If hardware resources are overcommitted to virtual machines, then resource utilization efficiency improves, but resource wastage increases when VMs are underutilized
Solution Approach 1:
The patent implements dynamic resource allocation by continuously monitoring VM resource usage and automatically adjusting the amount of hardware resources assigned to each VM based on actual utilization patterns. This transforms static resource allocation into a dynamic system that adapts to changing demands, resolving the contradiction between overcommitment efficiency and underutilization wastage.
Solution Approach 2:
The system employs feedback mechanisms by monitoring resource usage metrics and using this information to trigger automatic resource reallocation when usage falls below thresholds. This closed-loop control ensures resources are optimized based on actual demand, preventing both overprovisioning waste and underprovisioning performance issues.
2Measurement precision
If manual auditing is performed to identify underutilized VMs, then resource allocation accuracy improves, but labor requirements and operational complexity increase
Solution Approach 1:
The system performs self-service by automatically monitoring, evaluating, and reallocating resources based on predefined policies and thresholds. The hypervisor autonomously identifies underutilized VMs and adjusts resource allocation without requiring manual intervention, eliminating labor-intensive auditing while maintaining high allocation accuracy.
Solution Approach 2:
The patent changes the operational parameters from manual auditing processes to automated monitoring with configurable thresholds and policies. This transformation converts a labor-intensive manual process into an automated system that continuously optimizes resource allocation based on measurable usage parameters.
3Productivity
If resources are dynamically reallocated to underutilized VMs, then resource efficiency improves, but system stability may be affected by frequent changes
Solution Approach 1:
The system implements periodic action by monitoring resource usage at defined intervals and triggering reallocation only when sustained threshold violations occur. This periodic monitoring approach prevents reactive oscillations and ensures resources are adjusted based on sustained usage patterns rather than transient fluctuations, maintaining system stability while improving efficiency.
Solution Approach 2:
The system takes preliminary action by establishing predefined thresholds and policies before resource reallocation occurs. These pre-configured parameters guide the reallocation process, ensuring changes are made systematically and predictably rather than arbitrarily, which maintains system stability during dynamic resource optimization.
Data Source
AI summary
An amount of a hardware resource is assigned to a virtual machine (VM) to be run on a computing device including the hardware resource. The VM is caused to run on the computing device, and usage of the hardware resource by the VM is monitor. In response to determining that the usage of the hardware resource by the VM is less than a threshold, the amount of the hardware resource assigned to the VM is decreased.