Dynamic Virtual Machine Allocation for Computing Resource Optimization
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Solution Overview
Problem
Businesses face challenges in determining the optimal computing resources needed for workers, leading to either waste of resources or impairment of work functions due to insufficient capabilities, especially in traditional PC configurations and online service models.
Innovation Solution
The allocation of virtual machines (VMs) tailored to specific application requirements, with dynamic adjustment based on usage patterns and budget constraints, allowing for flexible provisioning and optimization of computing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If computing resources are provided to a worker that significantly exceed the computing requirements, then the worker's ability to perform work functions is improved, but resources are wasted
Solution Approach 1:
The patent implements dynamic resource allocation where virtual machine configurations are not fixed but can be adjusted based on actual usage patterns. The system monitors worker behavior and application requirements over time, then dynamically modifies computing resource allocation to match actual needs, preventing both waste and insufficiency
Solution Approach 2:
The system incorporates feedback mechanisms by monitoring worker usage patterns, application performance metrics, and resource consumption data. This feedback loop enables the system to continuously optimize resource allocation by comparing actual usage against allocated resources and making adjustments to eliminate waste while maintaining performance
2Loss of energy
If insufficient computing resources are provided to a worker, then resource waste is reduced, but the worker's ability to perform work functions is impaired
Solution Approach 1:
The system transitions from static resource allocation to dynamic allocation that adapts to changing work requirements. By continuously monitoring usage patterns and application demands, the system ensures resources are scaled appropriately to maintain productivity while avoiding over-provisioning
Solution Approach 2:
The patent changes the parameters of resource allocation by using multiple configuration profiles with different resource levels. The system selects and adjusts these parameters based on monitored usage patterns, enabling flexible optimization between resource efficiency and productivity
3Ease of operation
If traditional PC configurations are used for each worker, then computing resources are readily available, but it is difficult to determine the optimal configuration and resources may be wasted or insufficient
Solution Approach 1:
The patent introduces a virtual machine intermediary layer between the physical infrastructure and workers. This intermediary abstracts away the complexity of configuration determination by automatically managing resource allocation based on monitored usage patterns, while maintaining easy access to computing resources for workers
4Adaptability or versatility
If online service providers are used to provide computing resources on demand, then flexibility in adjusting computing resources is increased, but it is still difficult to determine the optimal amount of computing resources to provide
Solution Approach 1:
The system enhances online service provider models by implementing precise feedback mechanisms that monitor actual usage patterns at the application and user levels. This detailed feedback enables accurate determination of optimal resource amounts by comparing actual consumption against allocated resources, eliminating the imprecision of traditional demand-based models
Data Source
AI summary
Computing resources are provided to a user by identifying applications used by the user, and provisioning virtual computing resources that are adapted to the resource requirements of the identified applications. The resource requirements of the identified applications can be combined into a single set of resource requirements and used to acquire a virtual machine that is able to host the identified applications. In other examples, virtual machines may be acquired for each identified application. Each virtual machine generates a display stream via a streaming agent. The display stream is received by an application streaming client on the user's client computer system, and is displayed to the user on a client display. Multiple virtual machines may generate multiple display streams which can be combined by the application streaming client and presented to the user on the single client display.