Dynamic Erasure Coding Method for Reducing Storage Overhead in Blockchain Systems: Research Led by Minyi Guo

Research led by Minyi Guo, published in Frontiers of Computer Science on 12 Mar 2024, has made significant strides in addressing the challenge of reducing storage overhead in blockchain systems while maintaining data consistency and tolerating malicious nodes.

In traditional blockchain networks, full replication is used, where each node stores a complete copy of all blocks, leading to storage-intensive requirements as the blockchain grows. Previous approaches like BFT-Store and Partition Chain have utilized erasure codes to store blocks more efficiently by breaking data into smaller fragments with redundant parities distributed across multiple nodes.

The research team’s contribution lies in dynamically adjusting the encoding schema to tolerate malicious nodes more efficiently. By adapting the encoding schema based on the actual number of malicious nodes, unnecessary storage overhead associated with maintaining redundant parities can be reduced.

Their proposed method, Dynamic-EC, aims to reduce storage overhead in permissioned blockchain systems by adjusting the total number of parities according to the risk level of the system, determined by the number of perceived malicious nodes. This method consists of three modules: Node Classification, Dynamic Erasure Coding, and Adaptive Fragment Placement.

This research has the potential to improve the efficiency and scalability of blockchain networks, crucial as blockchain technology continues to evolve and find applications in various fields. The innovative approach taken by Minyi Guo and the research team could pave the way for more streamlined and secure blockchain systems in the future.