Execution Platform Determination via Resource Leveling Index
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Solution Overview
Problem
Existing execution platforms face inefficiencies in resource utilization due to diverse population coverage, leading to ineffective deployment of applications, as current methods do not optimize resource allocation across platforms.
Innovation Solution
An execution platform determination system that identifies actual and predicted resource usage statuses, calculates a leveling index to assess resource usage consistency, and determines the optimal platform for application deployment based on this index, ensuring efficient resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If applications are deployed using round robin method, then deployment simplicity is maintained, but resource utilization efficiency deteriorates
Solution Approach 1:
The system implements feedback by continuously monitoring actual resource usage status on execution platforms and using this information to predict future resource usage. The predicted resource usage status feeds back into the deployment decision-making process, allowing the system to select platforms that will maintain balanced resource utilization after new application deployments.
Solution Approach 2:
The system performs preliminary action by predicting the resource usage status before actually deploying applications. It calculates predicted resource usage for each execution platform and determines the optimal deployment target in advance, preventing resource imbalance before it occurs rather than reacting to it after deployment.
2Speed
If applications are deployed without considering resource usage patterns, then deployment speed is maintained, but resource allocation balance deteriorates
Solution Approach 1:
The system replaces manual or simple mechanical round-robin deployment methods with an intelligent prediction system that uses actual resource usage data to determine deployment targets. This substitution enables automated, data-driven decisions that maintain both deployment speed and resource allocation balance by selecting platforms based on predicted resource usage rather than fixed sequences.
3Measurement precision
If resource usage prediction is implemented for each execution platform, then resource utilization accuracy is improved, but system complexity increases
Solution Approach 1:
The system applies universality by using the same prediction methodology and evaluation criteria across all execution platforms. The prediction unit uses consistent actual resource usage data and applies uniform prediction logic to each platform, enabling accurate resource utilization assessment without requiring platform-specific complex models, thus maintaining system simplicity while achieving precision.
Data Source
AI summary
An AI/big-data processing module identifies, for each of a plurality of candidate platforms, a leveling index value indicating, in a case in which a to-be-added application has been constructed on the candidate platform, at least one of a degree of leveling of a resource usage status on the candidate platform or a degree of leveling of resource usage statuses among a plurality of the candidate platforms. A policy manager module determines, based on the leveling index value, an execution platform on which the to-be-added application is to be constructed from among the plurality of candidate platforms.