Efficient and Reliable Partitioning for Permissioned Blockchain: Two Multi-group Collaborative Storage Mechanisms

Blockchain, a promising distributed ledger for decentralization, plays a crucial role in JointCloud computing, offering secure data storage and sharing as well as reliable transaction tracking and resource allocation. While promising, it faces storage limitations due to its full-replication strategy. This issue has been addressed by scholars through storage partitioning mechanisms like BFT-Store and PartitionChain. These mechanisms leverage Erasure Coding with the Byzantine Fault Tolerant consensus protocol to overcome storage constraints. However, challenges persist: i) high computational complexity in encoding and decoding leading to prolonged computation time; ii) extensive use of verified signatures causing increased network message transmission and communication burden; iii) during system re-initialization, under-performing scalability and substantial time consumption due to the involving of all nodes in data decoding and re-encoding. To overcome these challenges, we propose two novel storage partitioning mechanisms (i.e., GPartition-Store and ParallelC-Store) for the permissioned blockchain that reduce the computational complexity of the coding processes by dividing nodes into multiple groups called storage units (SUs), avoid additional communication of generating verification proofs by employing the Bloom Filter, and improve the stability and scalability of the system by implementing the re-initialization process exclusively within a specific SU. Particularly, the computational complexity of encoding/decoding can be further degreased by about g²/g³ and g/g² compared to PartitionChain, by GPartition-Store and ParallelC-Store respectively (g is the number of SUs). Compared with the full-replication strategy, BFT-Store and PartitionChain, the experimental results demonstrate that the proposed mechanisms improve the Quality of Service (QoS) of the blockchain system including performance (i.e., efficiency and throughput), scalability and stability, while guaranteeing the availability.