Layered Resource Allocation Using Correlation-Based Quota Packaging

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Solution Overview

Problem

Existing methods struggle to accurately allocate resources across multiple consumers in a computing environment due to dynamic resource behavior, interdependencies, quality of service (QoS) guarantees, and changing resource overcommitment levels, leading to inefficiencies and inconsistent performance.

Innovation Solution

A method involving a resource model that predicts available quotas based on consumer configurations, generates correlation matrices, and subdivides resources into chunks for optimized allocation, considering consumer-specific patterns and interdependencies, ensuring reliable and efficient distribution.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If resource quotas are predetermined and partitioned before consumer startup, then allocation simplicity is improved, but accuracy of resource availability prediction deteriorates

Engineering Contradiction:

Improveallocation simplicityVSAvoidresource availability prediction accuracy

Core Design Contradiction:

Ease of manufactureVSMeasurement precision

Solution Approach 1:

The system performs preliminary actions by collecting resource utilization metrics and building correlation matrices before final quota allocation. This allows the system to predict resource availability more accurately while maintaining automated allocation processes.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback mechanisms by continuously monitoring resource utilization metrics and using correlation matrices to adjust quota allocations. This feedback loop enables accurate prediction of resource availability while maintaining allocation simplicity through automated decision-making.

Inventive Principle:

Principle #23Feedback

2Device complexity

If multiple resources are allocated independently, then allocation complexity is reduced, but resource interdependency utilization deteriorates

Engineering Contradiction:

Improveallocation complexityVSAvoidresource utilization efficiency

Core Design Contradiction:

Device complexityVSProductivity

Solution Approach 1:

The system merges multiple resource allocations by introducing correlation matrices that capture interdependencies between resources. Instead of allocating resources independently, the system combines allocation decisions based on observed correlations, improving overall resource utilization while maintaining manageable complexity through automated processing.

Inventive Principle:

Principle #5Merging (Combining)

3Adaptability or versatility

If resource overcommitment levels are changed over time, then adaptability to changing conditions is improved, but QoS guarantee reliability deteriorates

Engineering Contradiction:

Improveadaptability to changing conditionsVSAvoidQoS guarantee reliability

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system implements dynamic resource overcommitment levels that adjust over time based on observed resource utilization patterns and correlation matrices. This dynamic approach allows the system to adapt to changing conditions while maintaining QoS guarantees through data-driven decision-making and continuous monitoring.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system uses feedback from continuous monitoring of resource utilization metrics to adjust overcommitment levels while preserving QoS guarantees. The correlation matrices provide feedback on how changes in one resource affect others, enabling reliable adaptive management.

Inventive Principle:

Principle #23Feedback

4Speed

If resource quotas are assigned without considering consumer configuration, then allocation speed is improved, but accuracy of resource matching deteriorates

Engineering Contradiction:

Improveallocation speedVSAvoidresource quota accuracy

Core Design Contradiction:

SpeedVSMeasurement precision

Solution Approach 1:

The system performs preliminary analysis of consumer configurations and resource utilization patterns before making allocation decisions. By pre-computing correlation matrices and analyzing consumer-specific patterns, the system maintains fast allocation speeds while improving quota accuracy through informed decision-making.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20250355723A1Organizing utilization of resources in a computing environment

Publication Date: 2025.11.20 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

The invention relates to a computer-implemented method of organizing utilization of a plurality of resources in a computing environment logically partitioned in layers, the method comprising, by a computer system configured for implementing a first layer: identifying a plurality of consumers of the resources on a second layer subsequent to the first layer; for each of the resources: obtaining from a resource model a prediction of an available quota of the resource based on a configuration of the consumers; logically subdividing the available quota into chunks; for each of the consumers: obtaining a correlation matrix of utilization rates of each resource measured for the consumer; generating a resource package specific to the consumer, the generation comprising selecting, based on the correlation matrix, a number of the chunks obtained for each resource, and adding the selected chunks to the resource package; and allocating the resource package to the consumer.