Blockchain Node Feasibility Scoring System
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Solution Overview
Problem
Current blockchain networks lack a system to evaluate the suitability and feasibility of introducing a new node, as every type of node is not suitable to utilize the blockchain infrastructure, making it difficult to identify if a node can form or be part of a blockchain network.
Innovation Solution
A computer-implemented system that evaluates the feasibility of introducing a new node in a blockchain infrastructure using a memory, processor, database, query presentation module, input module, and assessment module, which includes feature detection, feature value assignment, criticality scoring, weightage assignment, and a feasibility evaluator to calculate a feasibility score.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a blockchain network allows any node to join, then network openness and accessibility are improved, but network security and data integrity deteriorate due to unsuitable nodes
Solution Approach 1:
The system performs preliminary evaluation of prospective nodes before they join the blockchain network. The assessment module evaluates nodes against predetermined rules covering technical capabilities, security measures, and operational parameters to determine suitability before node integration, preventing unsuitable nodes from compromising network security while maintaining openness
2Measurement precision
If comprehensive node evaluation is performed, then node suitability assessment is improved, but system complexity and evaluation time increase
Solution Approach 1:
The evaluation system is segmented into distinct modules: feature detector, feature value assignor, criticality assignor, weightage assignor, and feasibility evaluator. Each module handles specific aspects of node evaluation independently, making the complex assessment process manageable and scalable while maintaining comprehensive coverage of node suitability criteria
Solution Approach 2:
The system uses adjustable parameters including weightage scores and criticality scores that can be modified based on network requirements. This allows the evaluation criteria to be dynamically tuned to prioritize different aspects of node suitability without changing the fundamental evaluation architecture, balancing assessment precision with system simplicity
3Ease of operation
If manual node evaluation is used, then evaluation flexibility is improved, but evaluation efficiency and consistency deteriorate
Solution Approach 1:
The assessment module operates autonomously by automatically detecting node features, assigning values and weights according to predetermined rules, and generating feasibility scores without requiring manual intervention. This self-service approach maintains evaluation flexibility through configurable rules while dramatically improving efficiency and consistency compared to manual processes
Data Source
AI summary
The present disclosure envisages a system for evaluating the feasibility of introducing a new node in a blockchain infrastructure. The blockchain dimension queries and the transaction dimension queries are presented to a user. The user provides responses to the blockchain dimension queries and transaction dimension queries. A feature detector module detects features from the blockchain dimension responses and the transaction dimension responses. A feature value assignor assigns feature values to the detected features. A criticality assignor assigns criticality scores to the detected features. A weightage assignor assigns weightage scores to the blockchain dimension queries and the transaction dimension queries. The feasibility evaluator receives the feature values, the criticality scores, and the weightage scores, and calculates a feasibility score, thereby evaluating the feasibility of introducing the new node.