Sharding is one of the most promising technologies for significantly increasing blockchain transaction throughput. However, as the number of shards increases, the ratio of cross-shard transactions in existing blockchain sharding protocols gradually approaches 100%. Since cross-shard transactions consume many times more resources than intra-shard transactions, the processing overhead of cross-shard transactions already accounts for the majority of the total overhead of the sharding system. There is a very large gap between the transaction throughput of the sharding system and its theoretical upper limit. In this article, we propose Estuary, a novel low cross-shard blockchain sharding protocol. Taking the state model as an entry point, Estuary designs a multi-level state model and state splitting and aggregation mechanism. It decouples the identity and quantity of state units, enabling transactions between users to be completed within one shard. Only when the state quantity for all shards of a user is insufficient a small number of cross-shard transactions are required. On this basis, we propose a community overlap propagation algorithm for sharding. It defines the users’ belonging coefficients of each shard and optimizes the state distribution so that the state distribution can better match the transaction characteristics between users. Finally, we develop an analysis framework for the sharding protocol and experiment with real Bitcoin transactions. The evaluation results show that compared to the state-of-the-art sharding protocol, Estuary reduces the ratio of cross-shard transactions by 88.54% and achieves more than 1.85 times the throughput improvement (92.98% of the theoretical upper limit).

Sharding is a prevalent approach for addressing performance issues in blockchain. To reduce governance complexities and ensure system security, a common practice involves a relay chain to coordinate cross-shard transactions. However, with a growing number of shards and cross-shard transactions, the single relay chain usually first suffers from performance bottleneck and shows poor scalability, thus making the relay chain's scalability vital for sharding systems. To solve this, we proposeMitosis, the first multi-relay architecture to improve the relay chain's scalability by sharding the relay chain itself. Our proposed relay sharding algorithm dynamically adjusts the number of relays or optimizes the topology between relays and shards to adaptively scale up relay chain's performance. Furthermore, to guarantee the security of the multi-relay architecture, a new validator reconfiguration scheme is designed, accompanied by a comprehensive security analysis ofMitosis. Through simulation experiments on two mainstream relay chain paradigms, we demonstrate thatMitosiscan achieve high scalability and outperform state-of-the-art baselines in terms of workload of relays, relay chain throughput, and transaction latency.

Consensus algorithm is the core component of consortium blockchains. Equality, Unpredictability and Scalability are three important demands for the consensus algorithms of consortium blockchain. Existing deterministic consensus algorithms (e.g. PBFT) can ensure Equality, but cannot meanwhile meet Unpredictability and Scalability; probabilistic consensus algorithms (e.g. PoW) can achieve Scalability and guarantee a decent Unpredictability, but cannot meet the Equality requirement. In this paper, we propose a new consensus algorithm, namely Themis, which takes the three properties into account. Themis independently adjusts the block-producing difficulty of each node through a self-adaptive node election mechanism, effectively reducing the correlation between the block-producing frequency and the invested computing power of each node. Besides, a GEOST main chain consensus rule is proposed to handle forks and further improve the performance of the algorithm. If a fork occurs, consensus nodes will choose the sub-chain with the highest Equality to join the main chain. Evaluations show that Themis achieves outstanding performance in Equality and Unpredictability while ensuring Scalability, compared with the existing algorithms.