Dynamic Cloud VM Resource Allocation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current desktop virtualization systems face challenges in dynamically managing and optimizing resource allocation for virtual machines in cloud computing environments, leading to inefficiencies in resource utilization and potential performance issues.
Innovation Solution
The system determines resource usage levels and capacity for virtual machines and physical resources, allowing for dynamic configuration and reallocation of virtualization servers and physical resources to match virtual machines with optimal resources, update network traffic policies, and perform reconfiguration based on usage data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If desktop virtualization is implemented with centralized server management, then security and centralized control are improved, but resource utilization efficiency deteriorates
Solution Approach 1:
The patent implements dynamic resource allocation where virtual machine configurations are not fixed but can be automatically adjusted based on real-time resource usage metrics. The system continuously monitors CPU utilization, memory usage, and storage consumption, then dynamically modifies virtual machine parameters to optimize resource distribution across the virtualized environment, resolving the contradiction between centralized control and efficient resource utilization.
Solution Approach 2:
The system employs feedback mechanisms by monitoring resource usage levels and using this information to automatically adjust virtual machine configurations. The monitoring component collects data on resource consumption, feeds this information to the configuration adjustment logic, which then modifies virtual machine settings to improve overall resource utilization while maintaining security through centralized management.
2Stability of the object's composition
If fixed virtual machine configurations are used, then system stability is improved, but adaptability to changing resource demands deteriorates
Solution Approach 1:
The patent transforms fixed virtual machine configurations into dynamic ones that can adapt to changing resource demands. The system maintains stability by using controlled, incremental adjustments based on monitored resource usage patterns, allowing virtual machines to scale their resource allocation up or down automatically while preserving system stability through methodical configuration changes.
Solution Approach 2:
The system changes virtual machine configuration parameters such as CPU allocation, memory size, and storage capacity based on monitored resource usage. By adjusting these parameters dynamically rather than maintaining fixed settings, the system achieves both stability through controlled changes and adaptability to varying resource demands.
3Manufacturing precision
If manual resource allocation is performed, then configuration precision is improved, but operational complexity and time consumption deteriorate
Solution Approach 1:
The patent implements self-service automation where the virtualization system automatically monitors its own resource usage and performs configuration adjustments without manual intervention. The system self-manages the entire process of detecting resource imbalances, calculating optimal configurations, and applying changes, thereby eliminating time consumption associated with manual allocation while maintaining precision through algorithmic optimization.
Solution Approach 2:
The system uses continuous feedback from resource monitoring to automatically adjust configurations with precision. The feedback loop enables the system to detect usage patterns, calculate optimal resource分配, and implement precise configuration changes automatically, eliminating manual intervention while maintaining high configuration accuracy.
Data Source
AI summary
Virtual machines, virtualization servers, and other physical resources in a cloud computing environment may be dynamically configured based on the resource usage data for the virtual machines and resource capacity data for the physical resources in the cloud system. Based on an analysis of the virtual machine resource usage data and the resource capacity data of the virtualization servers and other physical resources in the cloud computing environment, each virtual machine may be matched to one of a plurality of virtualization servers, and the resources of the virtualization servers and other physical resources in the cloud may be reallocated and reconfigured to provide additional usage capacity to the virtual machines.