Computer System Upgrade Recommendation Method
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Solution Overview
Problem
Determining when and how to upgrade computer systems to improve performance is challenging due to rapid technological advances and the complexity of various component types, specifications, and costs, making it difficult to predict performance benefits and identify cost-effective upgrades.
Innovation Solution
A method that determines performance parameters of existing computer systems, obtains specifications for upgrade components, models upgrade scenarios, predicts performance parameters, and compares them to existing system parameters to quantify performance benefits and cost-effectiveness, recommending upgrades when beneficial.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If computer systems are upgraded with newer components to improve performance, then system performance increases, but system complexity and upgrade decision difficulty increase due to numerous component types, specifications, and vendors
Solution Approach 1:
The patent applies parameter changes by systematically varying component specifications (processor speed, memory capacity, storage type) in simulated upgrade scenarios to predict performance outcomes. The system models different parameter combinations to identify optimal upgrades without requiring manual evaluation of each component specification.
Solution Approach 2:
The patent uses virtual modeling and simulation to create copies of the existing system with proposed upgrade components. These digital twins allow performance prediction and comparison without physical installation, reducing the complexity of evaluating multiple upgrade scenarios across numerous component types and vendors.
2Measurement precision
If performance modeling is performed for multiple upgrade scenarios to predict performance benefits, then upgrade effectiveness can be quantified, but the time and computational resources required increase
Solution Approach 1:
The patent performs preliminary performance modeling by pre-establishing baseline performance parameters and component performance characteristics. This preliminary data collection and system characterization enables faster evaluation of subsequent upgrade scenarios, reducing the time required for each modeling iteration while maintaining measurement precision.
Solution Approach 2:
The patent creates a universal performance modeling framework that can evaluate multiple component types, vendors, and specifications using the same modeling approach. This multi-functional system handles diverse upgrade scenarios (processor upgrades, memory additions, storage upgrades) through a single integrated model, improving efficiency across different upgrade evaluations.
Data Source
AI summary
Method and computer program product for recommending cost effective upgrades for a computer system. At least one performance parameter is determined for an existing computer system. Up to date performance specifications for available upgrade components are obtained. A variety of potential systems are modeled utilizing at least one upgrade component, and at least one component from the existing system to create upgrade scenarios. At least one performance parameter is predicted for each upgrade scenario. The performance parameters for the upgrade scenarios are compared to the performance parameters of the existing computer system. The cost-effectiveness is determined for each upgrade scenario, and upgrade recommendations are made when the cost-effectiveness meets or exceeds a target value.