Erasure Coding Based Optimization in Decentralized Distributed Storage Systems

Node failures in decentralized distributed storage systems are common. To ensure data availability, these systems employ data redundancy mechanisms, typically relying on repli-cas. This paper proposes a decentralized data redundancy scheme based on erasure coding, with Reed-Solomon and IPFS as exam-ples. Compared with replication, the proposed scheme reduces storage space and enhances fault tolerance. Files are sharded and encoded across multiple nodes, avoiding the high redundancy of replicas. Users can retrieve any K shards from N nodes to reconstruct the original files. This erasure coding optimization combines efficient data exchange among decentralized nodes with erasure coding technology, significantly reducing storage space compared with the replica mechanism. The implementation involves truncating and sharding the blocks within the Merkle DAG generated by files, enabling flexible adjustments to the code rate of erasure codes and the allocation of storage nodes based on user needs and available resources. This method achieves a balance between storage efficiency and data availability.