Cloud Computing System Modeling via Hierarchical Indexing
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Solution Overview
Problem
Complex cloud computing systems are difficult to accurately model, which hinders performance analysis and optimization, as well as precise usage data collection for billing purposes.
Innovation Solution
A method involving assigning unique index values to objects within the cloud computing system, creating configuration values from these indices, and associating sub-index values based on characteristics like complexity and resiliency, with visualization through graphs or hypercubes to represent system data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If cloud computing system complexity increases, then system functionality and capabilities improve, but modeling accuracy and performance analysis capability deteriorate
Solution Approach 1:
The patent segments the complex cloud computing system into multiple hierarchical levels (infrastructure layer, platform layer, application layer) and models each level separately with appropriate detail. This allows accurate modeling of individual components while managing overall system complexity, resolving the contradiction between system functionality and modeling accuracy.
Solution Approach 2:
The patent introduces multiple dimensions for modeling including functional dimensions, performance dimensions, and organizational dimensions. By adding these dimensional perspectives, the system can maintain high functionality while achieving accurate modeling through multi-faceted representation rather than single-dimension oversimplification.
2Adaptability or versatility
If cloud computing system complexity increases, then system capabilities improve, but performance analysis and optimization capability deteriorate
Solution Approach 1:
The patent divides performance analysis into separate modular components that can be applied to different system layers independently. This segmentation enables efficient performance analysis of complex systems by breaking down the analysis task into manageable parts, maintaining productivity despite increased system capabilities.
Solution Approach 2:
The patent employs parameter-based modeling where system performance is represented through configurable parameters that can be adjusted and analyzed systematically. This allows performance analysis to scale with system complexity by changing the level of parameter detail rather than increasing analytical complexity proportionally.
3Adaptability or versatility
If cloud computing system complexity increases, then system functionality improves, but usage data collection precision for billing deteriorates
Solution Approach 1:
The patent segments usage data collection into specific transactional events at the application and platform layers, separate from infrastructure management. This allows precise tracking of billable usage events without being overwhelmed by overall system complexity, maintaining billing accuracy while supporting advanced system functionality.
Data Source
AI summary
A method for modeling a cloud computing system services performed by a physical computing system includes assigning, with the physical computing system, a unique index value from a number sequence to a number of objects of the cloud computing system; creating, with the physical computing system, a number of configuration values, each configuration value based on a combination of index values, each configuration value representing a unique combination of the objects associated with the cloud computing system; and associating, with the physical computing system, a number of sub-index values to each configuration value, the sub-index values being based on a characteristic of the unique combination of the objects indicated by the configuration value.