IT Resource Deployment Optimization with Cost and Importance Scoring
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Solution Overview
Problem
Existing IT resource optimization systems fail to consider cost reduction effects from migrating resources to different clouds and do not account for the importance of business units or applications, leading to inadequate recognition of reducible resources per unit and improper migration decisions.
Innovation Solution
A support apparatus and method that calculates optimal deployment locations and associated reducible costs for IT resources, considering both cost reduction and importance of allocation targets, allowing for informed decision-making on resource migration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If IT resources are migrated to optimize cost reduction, then cost savings are improved, but the importance of business units or applications may be compromised
Solution Approach 1:
The patent changes the evaluation parameters from单一的 cost metrics to a multi-dimensional parameter system that includes cost reduction effects, business unit importance, and application criticality. This allows resources to be evaluated and migrated based on a balanced scorecard rather than cost alone, resolving the contradiction between cost optimization and business importance preservation.
Solution Approach 2:
The patent implements a feedback mechanism where the evaluation results are presented to users who can then adjust migration decisions based on business priorities. The system provides feedback loops that allow continuous refinement of migration strategies, ensuring that cost reduction goals are pursued while respecting business unit importance and application criticality constraints.
2Productivity
If all IT resources are evaluated for migration based on cost reduction, then cost optimization is improved, but the complexity of decision-making increases
Solution Approach 1:
The patent segments the IT resource evaluation process into distinct modules: cost reduction calculation, business unit importance assessment, application criticality evaluation, and migration recommendation generation. This segmentation allows each aspect to be handled independently and systematically, reducing overall decision-making complexity while maintaining comprehensive cost optimization.
Solution Approach 2:
The patent introduces an intermediary evaluation system that acts as a mediator between cost optimization goals and migration execution. This intermediary layer processes multiple evaluation criteria and translates them into actionable migration recommendations, simplifying the decision-making process by providing structured guidance rather than raw data alone.
3Loss of energy
If deployment optimization is performed without considering business unit importance, then cost reduction is improved, but the ability to make informed migration decisions deteriorates
Solution Approach 1:
The patent creates a universal evaluation framework that simultaneously handles multiple functions: cost reduction calculation, business unit importance assessment, application criticality evaluation, and migration recommendation generation. This multi-functional system ensures that no information is lost while pursuing cost reduction, as all relevant factors are integrated into a single comprehensive evaluation process.
Data Source
AI summary
A support apparatus and method are capable of facilitating work to optimize deployment locations of information processing resources and are respectively allocated to one or more allocation targets. A deployment location candidate is calculated, which is an appropriate deployment location of each of the information processing resources allocated to each of the allocation targets, and a reducible cost is determined when the information processing resource is allocated to the deployment location candidate, with respect to each information processing resource. The reducible cost is displayed when the deployment of the information processing resource allocated to the allocation target is optimized, and the importance of the allocation target is determined by associating the reducible cost with the importance of the allocation target with respect to each allocation target on the basis of the calculation result of the reducible cost for each information processing resource.