Multi-Criteria Decision Analysis for Virtual Resource Prioritization

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Solution Overview

Problem

Existing information processing systems face challenges in efficiently managing and prioritizing virtual computing resources, particularly in cloud-based environments, due to the lack of intelligent methods for scheduling operations such as shutdowns, backups, and workload allocation, which are often manual and inefficient.

Innovation Solution

The implementation of a multi-criteria decision analysis (MCDA) algorithm that determines prioritization of virtual computing resources based on directional correlations between selected criteria, using techniques like Mahalanobis distance to generate relative closeness ratings, enabling intelligent scheduling operations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual scheduling methods are used for virtual computing resources, then ease of operation is maintained, but productivity is reduced due to inefficiency

Engineering Contradiction:

Improvescheduling efficiencyVSAvoidmanual intervention requirement

Core Design Contradiction:

ProductivityVSEase of operation

Solution Approach 1:

The system enables automated self-service scheduling by implementing an intelligent agent that autonomously evaluates virtual computing resources against multiple criteria (service level agreements, resource utilization, dependencies) and automatically generates prioritization rankings without requiring manual intervention, thereby resolving the contradiction between productivity improvement and ease of operation

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical scheduling operations with an automated computational system that uses multi-criteria decision analysis algorithms and machine learning models to evaluate and prioritize virtual computing resources, substituting human-operated mechanical processes with automated electronic decision-making systems

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If simple scheduling criteria are used, then ease of operation is improved, but measurement precision is reduced in prioritizing resources

Engineering Contradiction:

Improveprioritization accuracyVSAvoidcriteria evaluation complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent segments the complex prioritization problem into distinct evaluable criteria (service level agreement compliance, resource utilization metrics, inter-resource dependencies, performance indicators) that can be independently measured and weighted, allowing precise multi-dimensional evaluation while managing complexity through structured decomposition

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system dynamically adjusts evaluation parameters and criteria weights based on changing system conditions, service level agreements, and resource states, enabling precise prioritization that adapts to varying operational requirements while maintaining manageable complexity through parameter optimization

Inventive Principle:

Principle #35Parameter changes

3Productivity

If automated scheduling is implemented, then productivity is improved, but device complexity increases due to algorithm implementation

Engineering Contradiction:

Improveresource management efficiencyVSAvoidalgorithm processing complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent introduces intermediary components including intelligent agents, brokers, and abstraction layers that mediate between the complex multi-criteria decision analysis algorithms and the actual scheduling operations, shielding the system from algorithmic complexity while enabling automated high-productivity resource management

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system implements dynamic scheduling algorithms that adaptively adjust evaluation criteria, weights, and decision-making parameters based on real-time system state, service level agreements, and resource utilization patterns, enabling automated productivity improvement while managing complexity through dynamic optimization rather than static rigid algorithms

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS11822953B2Multi-Criteria decision analysis for determining prioritization of virtual computing resources for scheduling operations

Publication Date: 2023.11.21 DELL PROD LP

AI summary

An apparatus comprises a processing device configured to select prioritization criteria for a plurality of virtual computing resources and to determine, for at least one criterion in the selected prioritization criteria, at least one directional correlation between the at least one criterion and at least one other criterion in the selected prioritization criteria. The processing device is also configured to generate a prioritization of the plurality of virtual computing resources utilizing a multi-criteria decision analysis algorithm. The multi-criteria decision analysis algorithm is based at least in part on the determined at least one directional correlation. The processing device is further configured to perform one or more scheduling operations for the plurality of virtual computing resources based at least in part on the generated prioritization of the plurality of virtual computing resources.