ABSTRACT Blockchain sharding has emerged as a promising solution to address the scalability challenges of modern blockchain systems, yet in practice, existing sharding systems still suffer from serious performance bottlenecks. In recent work, LB‐Chain proposes a framework for load balancing by dynamically migrating hot accounts, which significantly improves throughput and latency. However, the approach still suffers from the computational overhead associated with frequent full ordering, which limits its efficiency in large‐scale systems. To address this issue, this paper proposes an enhanced sharding framework, DH‐Chain, which improves computational efficiency by introducing heap sorting optimization, dynamically managing the load of sharding and accounts, and avoiding full‐volume sorting during each round of migration. The experimental results show that DH‐Chain achieves 3.2% higher throughput than LB‐Chain and 11.4% higher than random allocation, approaching the theoretical upper bound of ideal allocation. By leveraging heap‐based sorting and two‐phase commit protocols, DH‐Chain ensures atomicity and security while reducing computational overhead. The framework effectively balances shard loads, maintaining consistent performance across varying transaction loads and demonstrating robust scalability.
Wang et al. (Sun,) studied this question.