Blockchain Validator Feedback Mechanism for Consensus Bottlenecks
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Solution Overview
Problem
The increasing number of validator nodes in blockchain systems leads to a performance bottleneck due to longer times to reach consensus, which decreases transaction throughput and can be exacerbated by the presence of Byzantine fault tolerance scenarios, where malicious or erroneous votes require additional identical votes to progress consensus.
Innovation Solution
A built-in feedback mechanism is implemented to sanction validator nodes that consistently vote against the ultimate consensus, using a feedback registry to track 'bad' votes and apply sanctions such as reduced voting weight or temporary bans when a predetermined threshold is reached, thereby isolating inconsistent nodes and speeding up the consensus process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the number of validator nodes is increased to enhance security and consensus reliability, then the system becomes more robust against Byzantine faults, but the time required to reach consensus increases significantly
Solution Approach 1:
The patent implements a feedback mechanism where validator nodes receive feedback about their voting behavior and receive sanctions when they consistently vote against the ultimate consensus. This feedback loop creates a self-regulating system that reduces the need for additional validation rounds, thereby decreasing consensus time while maintaining reliability through targeted sanctions rather than universal validation.
Solution Approach 2:
The patent extracts and isolates problematic validator nodes through the sanctioning mechanism. By identifying and separating inconsistent validators from the consensus process, the system reduces the effective number of validators needed for consensus, thereby decreasing consensus time while maintaining security through the removal of malicious or erroneous voters.
2Productivity
If validator nodes are sanctioned to reduce consensus time, then transaction throughput improves, but the complexity of the validation system increases
Solution Approach 1:
The feedback mechanism automates the sanctioning process by automatically tracking validator voting patterns and applying pre-defined sanctions when thresholds are met. This automation reduces the manual intervention and complex decision-making required in the validation system, maintaining productivity improvement while limiting complexity growth through rule-based automation.
Solution Approach 2:
The system performs preliminary tracking and evaluation of validator voting behavior before sanctions are applied. By pre-establishing feedback loops and sanction thresholds, the system avoids complex real-time decision-making during consensus, thereby improving throughput while managing system complexity through advance preparation of validation rules.
Data Source
AI summary
The system, method, and computer program product described herein provides a built-in feedback mechanism for a blockchain to sanction validator nodes that consistently “vote” in a manner that does not match the ultimate consensus. The method includes receiving a vote on whether to add a transaction to the blockchain, comparing the vote to a consensus decision on whether to add the transaction to the blockchain, determining based on the comparison that the vote does not match the consensus decision, in response to determining that the vote does not match the consensus decision, incrementing a value associated with the validator node in a feedback registry, determining that the value associated with the validator node is above a predetermined threshold value, and in response to determining that the value associated with the validator node is above the predetermined threshold, proposing a sanction of the validator node to the plurality of validator nodes.