Partitioned Blockchain Ledger Parallel Transaction Processing
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Solution Overview
Problem
Blockchain networks face inefficiencies in processing high-frequency transactions due to the need for consensus among all peers, which slows down the transaction processing time as the number of peers increases, limiting their capacity to handle multiple transactions simultaneously.
Innovation Solution
Partitioning the blockchain ledger into multiple partitions, where each transaction is assigned a partition code and processed independently by peers within its designated partition, allowing for parallel processing and reducing the need for consensus across all peers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all peers participate in consensus for every transaction, then security and decentralization are maintained, but transaction processing speed decreases
Solution Approach 1:
The blockchain network is segmented into multiple partitions, where each partition processes transactions independently. This segmentation allows transactions to be processed in parallel across different partitions rather than requiring all peers to reach consensus on every transaction, thereby improving processing speed while maintaining security within each partition through localized consensus mechanisms.
2Quantity of substance
If the number of peers increases, then network capacity and decentralization improve, but consensus time increases
Solution Approach 1:
By dividing the peer network into multiple partitions, each with its own consensus process, the system can accommodate more peers without proportionally increasing consensus time. Each partition reaches consensus independently and in parallel, so adding peers to the overall network capacity does not linearly increase the time required for any single consensus operation.
Solution Approach 2:
The patent introduces a new dimension of parallelism by organizing peers into multiple independent partitions that operate simultaneously. This dimensional change from sequential consensus to parallel partitioned consensus allows the system to scale peer quantity without proportionally increasing consensus time, as multiple consensus processes occur concurrently across different partitions.
3Measurement precision
If sequential transaction processing is used, then consensus accuracy is maintained, but transaction throughput decreases
Solution Approach 1:
The transaction processing system is segmented into multiple independent partitions that process transactions in parallel. Each partition maintains consensus accuracy through its own validation and agreement protocols, while the overall system achieves higher throughput by simultaneously processing multiple transactions across different partitions rather than sequentially.
Data Source
AI summary
An example operation may include one or more of identifying partitions associated with a blockchain, identifying a new transaction to be committed to the blockchain, determining a partition code assigned to the new transaction, and committing the new transaction to one of the partitions associated with the partition code.


