Publication | Closed Access
S-Store: A Scalable Data Store towards Permissioned Blockchain Sharding
30
Citations
17
References
2022
Year
Cluster ComputingBlockchain Consensus ProtocolEngineeringStorage StructureCommittee AdditionHardware SecurityKeyvalue DatabaseBlockchain ShardingParallel ComputingMerkle Tree ReconstructionData ManagementMerkle TreesComputer EngineeringData PrivacyComputer ScienceData SecurityCryptographyCloud ComputingBlockchain ScalabilityDistributed Data StoreBlockchainBlockchain Protocol
Sharding technique, which divides the whole network into multiple disjoint groups or committees, has been recognized as a revolutionary solution to enhance the scalability of blockchains. For account-based model, state data are partitioned over all committees and organized as Merkle trees to ensure data consistency and immutability. However, existing techniques on Merkle tree-based state storage fail to scale out due to a large amount of network and compute overheads incurred by data migration and Merkle tree reconstruction, respectively. In this paper, we propose $\mathcal{S}$-Store, a scalable data storage technique towards permissioned blockchain sharding based on Aggregate Merkle B+ tree (AMB-tree). $\mathcal{S}$-Store utilizes consistent hashing to reduce data migration among committees and uses split and merge on AMB-tree to decrease Merkle tree reconstruction overheads. $\mathcal{S}$-Store also employs a novel committee addition protocol that guarantees the system service availability during data migration. Extensive experiments show that $\mathcal{S}$-Sotre outperforms existing techniques by one order of magnitude in terms of transaction execution, data transmission, and committee addition.
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