Service Provider Selection via Unstructured Data Reliability Scoring
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Solution Overview
Problem
Existing methods for determining optimal service providers in cloud federation environments falter when faced with complex client requirements and constraints, particularly due to the integration of structured and unstructured Quality of Service (QoS) data.
Innovation Solution
A computer-implemented method that receives client requirements, analyzes available service providers, identifies and evaluates unstructured external data sources for reliability, adjusts provider scoring based on this reliability, and provides an optimal selection of service providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If unstructured external data sources are integrated into service provider analysis, then the comprehensiveness of QoS data is improved, but the reliability assessment complexity increases
Solution Approach 1:
The patent introduces an intermediary reliability scoring mechanism that mediates between unstructured external data sources and service provider evaluation. The system assigns reliability scores to external data sources and uses these scores to weight the information they provide, thereby managing the complexity of integrating multiple unstructured sources while improving overall QoS assessment reliability.
Solution Approach 2:
The patent transforms unstructured external data into structured evaluations by introducing parameter-based reliability scoring. External data sources are assessed using defined parameters (reliability metrics), and this structured approach allows the system to handle unstructured information in a systematic manner, reducing analysis complexity while maintaining comprehensiveness.
2Measurement precision
If multiple data sources are analyzed for service provider selection, then the accuracy of provider scoring is improved, but the processing time increases
Solution Approach 1:
The patent implements a partial action approach by analyzing only the most relevant and reliable data sources for each service provider evaluation. The system dynamically selects which external data sources to analyze based on their reliability scores and relevance to specific service requirements, thereby achieving accurate provider scoring without processing all available data sources, thus reducing analysis time.
Solution Approach 2:
The patent performs preliminary analysis by pre-assessing and ranking external data sources based on their reliability metrics before the actual service provider selection process. This preliminary action allows the system to quickly identify and focus on high-quality data sources during provider evaluation, improving scoring accuracy while minimizing the time required for data analysis.
3Reliability
If reliability adjustment mechanisms are implemented, then the robustness of service selection is improved, but the system complexity increases
Solution Approach 1:
The patent uses parameter changes to implement reliability adjustment through standardized reliability scoring parameters. By defining specific parameters for assessing data source reliability and systematically applying these parameters across all evaluations, the system achieves robust service selection with a manageable level of complexity through consistent parameter-based adjustment.
Solution Approach 2:
The patent creates a universal reliability adjustment mechanism that serves multiple functions: it assesses data source quality, weights information from external sources, adjusts service provider scores, and validates selection robustness. This multi-functional approach improves service selection reliability while avoiding the need for separate complex mechanisms for each function.
Data Source
AI summary
A computer implemented method for selecting service providers includes receiving a set of client requirements and analyzing available service providers based on the received set of client requirements. The method additionally includes scoring the available service providers based on the analysis. The method further includes identifying one or more unstructured external data sources corresponding to the available service providers and analyzing the reliability of the one or more unstructured external data sources with respect to the available service providers. The method further includes adjusting the scoring of the service providers based, at least in part, on the data source reliability, and subsequently providing an optimal selection of service providers based on the adjusted scoring. A computer program product and computer system corresponding to the method are also disclosed.