Remote Services Selection Engine for Provider Evaluation
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Solution Overview
Problem
In distributed computing systems, selecting the appropriate remote service provider among multiple providers is challenging, especially when multiple providers offer the same service, requiring a method to evaluate and rank providers based on various criteria, which can be difficult and costly to implement within core programs.
Innovation Solution
A remote services selection engine calculates scores for each provider based on evaluation criteria, including financial, security, legal, and environmental information, using a trustworthiness measure and weighting scheme, and applies cognitive analysis techniques like natural language processing to select the best provider.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple providers are used to provide the same remote service, then service availability and competition are improved, but selection complexity and evaluation difficulty increase
Solution Approach 1:
The patent introduces a remote services selection engine as an intermediary component that sits between the core program and multiple remote service providers. This selection engine automatically evaluates providers based on predefined criteria (financial, security, legal, environmental) and selects the most appropriate provider, thereby managing the complexity of multi-provider selection without requiring the core program to handle it directly.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring provider performance and updating evaluation scores based on ongoing assessments. This allows the selection engine to adapt to changing provider qualities and make informed decisions, reducing selection complexity through automated feedback loops rather than manual evaluation.
2Measurement precision
If comprehensive evaluation criteria are applied to select remote services, then selection quality is improved, but processing time and computational resources increase
Solution Approach 1:
The patent applies preliminary action by pre-establishing evaluation criteria frameworks and provider profiles before actual service selection is needed. Financial, security, legal, and environmental criteria are predefined and weighted in advance, allowing the selection engine to quickly score providers against these predetermined standards rather than evaluating each criterion from scratch during selection.
Solution Approach 2:
The system changes parameters by dynamically adjusting evaluation weights and thresholds based on service type and organizational priorities. This allows the comprehensive evaluation to be tailored and optimized for different scenarios, reducing unnecessary processing while maintaining selection quality through parameter optimization.
3Productivity
If automated selection systems are implemented, then operational efficiency is improved, but system complexity and development costs increase
Solution Approach 1:
The remote services selection engine is designed as a universal, multi-functional platform that can evaluate multiple providers across multiple criteria (financial, security, legal, environmental) using a single integrated system. This universal approach consolidates what would otherwise require multiple separate evaluation systems, achieving automation efficiency without proportionally increasing overall system complexity.
Solution Approach 2:
The system segments the complex selection process into distinct, manageable modules: information collection, criteria evaluation, scoring calculation, and provider selection. Each module handles a specific aspect of the evaluation, making the overall automated system more manageable and easier to implement than a monolithic solution, thereby reducing development complexity while maintaining operational efficiency.
Data Source
AI summary
Embodiments for selecting a remote service for a core program are provided. A request for a remote service is received. Information associated with each of a plurality of remote services is received from at least one information source. A score for each of the plurality of remote services is calculated based on the information associated with each of the plurality of remote services and at least one remote service evaluation criteria.