Decentralized Cloud Service Assessment via Error Confirmation Capsules
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Solution Overview
Problem
Cloud service assessments are often unreliable due to one-sided provider information and the burden of manually gathering and analyzing data from multiple sources, making comparative analyses of competing cloud services challenging.
Innovation Solution
A system that automatically generates and analyzes technical performance data from cloud service events, using a blockchain-enabled network to provide trusted, transparent, and immutable assessments, including error confirmation capsules, performance indicia, and comparative rankings of cloud service providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If cloud service assessments rely on provider-provided information, then the assessment process is simple, but the reliability and objectivity of the assessment deteriorates
Solution Approach 1:
The patent introduces an intermediary assessment system that collects performance data from multiple independent sources (clients, third-party monitoring services, public repositories) rather than relying solely on provider-provided information. This intermediary layer aggregates and validates data from diverse sources to produce objective assessments, resolving the contradiction between simplicity and reliability by automating the data collection and analysis process.
2Measurement precision
If cloud service assessments manually gather data from multiple sources, then the comprehensiveness of the assessment improves, but the time and resource consumption increases
Solution Approach 1:
The patent implements preliminary action by pre-configuring automated data collection mechanisms that continuously monitor and store performance metrics from multiple sources before assessments are needed. Error confirmation capsules are pre-generated and stored in distributed repositories, allowing rapid retrieval and analysis during assessment events without manual data gathering, thus achieving comprehensive assessments efficiently.
Solution Approach 2:
The patent replaces manual mechanical data gathering processes with automated electronic systems. Software agents continuously collect performance data, error logs, and metrics from cloud services and store them in distributed repositories. This automation eliminates manual intervention, reducing time consumption while maintaining comprehensive data collection across multiple sources.
3Device complexity
If cloud service assessments use centralized data collection, then the analysis process is simplified, but the security and trustworthiness of the assessment deteriorates
Solution Approach 1:
The patent segments the assessment system into distributed components: data collection agents deployed across multiple locations, distributed repositories for storing error confirmation capsules, and independent validation nodes. This segmentation prevents single-point failures and manipulation, enhancing trustworthiness while maintaining analytical simplicity through standardized data formats and automated processing rules at each segment.
Solution Approach 2:
The patent introduces intermediary validation layers that mediate between raw data sources and final assessments. Independent validation nodes verify error confirmation capsules against predefined criteria and cross-reference multiple data sources before incorporating results into assessments. This intermediary validation mechanism enhances trustworthiness by preventing manipulation while keeping the overall analysis process automated and relatively simple.
Data Source
AI summary
Decentralized cloud service assessment includes using a self-executing data structure, an error confirmation capsule (ECC) generated in response to a cloud service failure experienced by a cloud service client (CSC). One or more technical performance indicia corresponding to the cloud service failure are extracted from the ECC in response to the validating. The one or more technical performance indicia are compared to one or more electronically stored predefined performance norms of a cloud service provider (CSP) associated with the cloud service failure. Based on the comparing, a comparative ranking of the CSP is determined. A graphical user interface display is generated based on comparative rankings of the CSP and one or more other CSPs.