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Adaptive online blockchain sharding algorithm based on trusted execution environments
Fei WANG, Hengdi WANG, Konglin ZHU, Lin ZHANG
Journal of Computer Applications    2025, 45 (11): 3424-3431.   DOI: 10.11772/j.issn.1001-9081.2024121839
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Aiming at the performance bottleneck caused by multi-round inter-shard communication in cross-shard transaction protocols, an adaptive online blockchain sharding algorithm based on Trusted Execution Environments (TEE) was proposed. The algorithm optimizes the execution process of cross-shard transactions, reducing communication overhead and improving system throughput. Firstly, an adaptive online sharding algorithm was designed, which delayed the allocation time of transactions to shards, allowing related transactions to be clustered together, thereby reducing the number of cross-shard transactions and minimizing communication overhead. Secondly, by combining TEE technology, off-chain cross-shard transactions were securely and efficiently executed, eliminating the need for multi-round inter-shard communication in traditional schemes. Finally, a one-sided feedback optimization algorithm was introduced to dynamically adapt to changes in transaction patterns based on current system status and transaction demands, optimizing the sharding strategy in real time. Experimental results showed that compared with the random sharding algorithm, the proposed algorithm increased throughput by 35%. By reducing unnecessary communication and computational overhead, the proposed algorithm significantly improves overall system performance, while ensuring the security of cross-shard transactions. It is suitable for blockchain systems requiring high throughput and low latency, and has considerable application value.

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