摘要： 区块链因其不可篡改、可追溯等特性，为数据存储和交易提供了透明度和安全保障，在金融、民生服务与公共管理等领域展现了其广泛适用性。随着区块链技术在多元化应用场景中的深度渗透，其底层架构需要应对海量数据存储与高频交易处理的双重压力。为突破区块链系统的扩展性瓶颈，区块链分片技术应运而生，其通过分布式并行计算机制有效提升了系统整体吞吐量，这一技术已在以太坊2.0中获得成功验证。然而，当前区块链网络分片中仍存在跨分片交易频繁、重配置开销大和分片间负载不均的问题。针对这些问题，本文提出基于增量图划分的区块链动态网络分片策略，将增量图划分技术用于划分区块链网络交易图，根据网络中节点的变化适时调整分片，在新节点加入交易图中时只处理新增部分，无需从头开始重新划分，降低了跨分片交易比例，更适应区块链网络的动态变化；提出一种动态分片负载优化算法（DSLO，Dynamic Sharding Load Optimization Algorithm）计算交易在各分片上的权值，在算法中引入频时计数器（LFU-TTL，Least Frequently Used - Time To Live），通过结合交易频率和存活时间预测分片负载情况，优化负载均衡。实验结果表明，本方案能有效降低跨分片交易比例、分片重配置时的数据复制成本，改善分片间的负载均衡。

Abstract: Due to its tamper proof and traceable characteristics, blockchain provides transparency and security guarantees for data storage and transactions, demonstrating its wide applicability in fields such as finance, livelihood services, and public management. With the deep penetration of blockchain technology in diversified application scenarios, its underlying architecture needs to cope with the dual pressure of massive data storage and high-frequency transaction processing. To overcome the scalability bottleneck of blockchain systems, blockchain sharding technology has emerged, which effectively improves the overall throughput of the system through distributed parallel computing. This technology has been successfully validated in Ethereum 2.0. However, there are still issues with frequent cross shard transactions, high reconfiguration costs, and uneven load between shards in current blockchain network sharding. In response to these issues, this article proposes a blockchain dynamic network sharding strategy based on incremental graph partitioning. The incremental graph partitioning technique is used to partition the blockchain network transaction graph, and the sharding is adjusted in a timely manner according to the changes in nodes in the network. When a new node is added to the transaction graph, only the newly added part is processed, without the need to re partition from scratch, reducing the proportion of cross shard transactions and better adapting to the dynamic changes of the blockchain network; Propose a Dynamic Sharding Load Optimization Algorithm (DSLO) to calculate the weights of transactions on each shard, and introduce a Frequency Time Counter (LFU-TTL) into the algorithm to predict shard load by combining transaction frequency and survival time, optimizing load balancing. The experimental results show that this scheme can effectively reduce the proportion of cross shard transactions, data replication costs during shard reconfiguration, and improve load balancing between shards.