Configurable Virtual Machines Dynamic Resource Pricing
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Solution Overview
Problem
Current remote computing services lack flexibility and cost-effectiveness in allowing users to dynamically select and customize computing resources, as they often require fixed resource allocations and pricing models that do not account for real-time availability and utilization.
Innovation Solution
A system where configuration servers generate configuration files based on user-selected resources, allowing users to choose from dynamically available computing resources, with pricing adjusted according to availability and utilization, enabling customizable virtual machines and flexible resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If fixed resource allocations are used in remote computing services, then service stability is improved, but flexibility and adaptability deteriorate
Solution Approach 1:
The patent implements dynamic resource allocation by allowing users to select and configure computing resources in real-time based on availability and pricing. The system dynamically adjusts resource allocation without requiring service interruption, enabling both stability through continuous service and flexibility through user-selected configurations.
Solution Approach 2:
The system enables parameter changes by allowing users to modify computing resource configurations (CPU, memory, storage) according to changing needs. Pricing models are adjusted based on real-time availability and utilization parameters, enabling the system to adapt while maintaining stable service delivery.
2Ease of operation
If fixed pricing models are used, then pricing simplicity is improved, but cost-effectiveness and adaptability deteriorate
Solution Approach 1:
The pricing model dynamically adjusts based on real-time resource availability and utilization metrics. Users are presented with current pricing information that reflects actual system state, enabling cost-effective selections while maintaining operational simplicity through automated price presentation and configuration generation.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring resource utilization and availability, then using this information to adjust pricing in real-time. This feedback loop enables the system to optimize cost-effectiveness while presenting simplified pricing options to users based on current system conditions.
3Adaptability or versatility
If users can dynamically select resources, then flexibility and customization are improved, but system complexity increases
Solution Approach 1:
The patent introduces configuration servers as intermediaries that manage the complexity of dynamic resource selection. These servers handle resource availability tracking, pricing calculations, and configuration file generation, shielding users from underlying system complexity while enabling extensive customization capabilities.
Solution Approach 2:
The system enables self-service through automated configuration file generation based on user selections. The configuration servers automatically process resource selections, calculate pricing, and generate ready-to-deploy configurations, reducing the complexity burden on users while maintaining high customization levels.
4Adaptability or versatility
If real-time pricing and availability tracking are implemented, then cost optimization is improved, but information processing requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-calculating and presenting pricing information based on current resource availability before user selection. Configuration servers prepare multiple pricing scenarios and availability states in advance, reducing the information processing burden during actual user interactions while maintaining real-time cost optimization capabilities.
Data Source
AI summary
Systems and methods for configuring a virtual machine provided by a remote computing system based on the availability of one or more remote computing resources and respective corresponding prices of the one or more remote computing resources are disclosed. Users are presented with an interface that allows for selection of individual remote computing resources to be included in a custom-configured virtual machine. Also, a customized corresponding price is determined for the custom-configured virtual machine based on user selections and current availability of the selected remote computing resources to be included in the custom-configured virtual machine.