Hub-Mediated Data Processing for Consensus and Order
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Implementing shared services efficiently and reliably without relying on a central entity, where multiple data processing apparatuses managed by different entities need to agree on request processing to ensure accuracy and prevent discrepancies.
Innovation Solution
A system where multiple data processing nodes communicate through a hub, ensuring all nodes process requests in the same order by forwarding requests through the hub, and using cryptographic hashes to achieve consensus on the processing outcomes, ensuring that transactions are correctly recorded in a shared ledger without the need for a central management entity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple data processing nodes operate independently without a central entity, then system reliability and trust are improved, but system complexity and coordination difficulty increase
Solution Approach 1:
The patent introduces a hub as an intermediary component that mediates communication between multiple data processing nodes. The hub receives requests from nodes, ensures they are processed in the same order, and distributes them appropriately, thereby reducing the complexity of direct peer-to-peer coordination while maintaining the benefits of decentralized operation.
Solution Approach 2:
The system is segmented into distinct functional components: multiple independent data processing nodes for computation and a central hub for coordination. This segmentation allows each node to operate independently for reliability while the hub handles the coordination complexity separately.
2Productivity
If requests are processed in parallel by multiple nodes, then processing speed is improved, but consistency and accuracy of processing outcomes deteriorate
Solution Approach 1:
The hub performs preliminary ordering of requests before distributing them to nodes. By establishing a predetermined processing order at the hub level, the system enables parallel execution at the node level while maintaining consistency in the processing sequence, thus achieving both speed and accuracy.
Solution Approach 2:
The system incorporates feedback mechanisms where nodes report their processing results back to the hub, which then verifies consistency across nodes. This feedback loop ensures that parallel processing outcomes are consistent and accurate while maintaining high processing throughput.
3Measurement precision
If cryptographic hashes are used to verify consensus, then processing accuracy is improved, but computational overhead and time consumption increase
Solution Approach 1:
The system uses cryptographic hashes selectively and efficiently, applying them only where necessary for verification rather than at every processing step. This partial application maintains high accuracy for critical verification points while reducing overall computational overhead and time consumption.
Data Source
AI summary
A first data processing device can include circuitry configured to receive an electronic request message; generate first electronic information using the electronic request message; receive, from each of one or more second data processing devices, respective first characteristic data of respective second electronic information generated by that second data processing device; generate, for each of the one or more second data processing devices, respective second characteristic data of the first electronic information; compare, for each of the one or more second data processing devices, the first characteristic data with the second characteristic data; and when one or more matches between the first characteristic data and second characteristic data for the one or more second data processing devices meet a predetermined condition, perform a predetermined process using the first electronic information in response to the electronic request message.