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March 16, 2026· IEEE Transactions on Computers
article

RollShard: Atomic Multi-Shard Transactions via Verifiable Stateless Off-Chain Processing

Authors:Dengcheng HuJianRong WangHao XuXiulong LiuWenyu Qu

Abstract

Ensuring atomic execution of cross-shard transactions is a fundamental challenge for sharded blockchains, particularly in scenarios demand coordination across multiple shards. However, existing solutions either rely on on-chain coordination, leading to high communication overhead, or leverage secure hardware for off-chain execution, imposing strong trust assumptions and reducing general applicability. To this end, we propose RollShard, a sharded blockchain that integrates stateless off-chain mechanism to efficiently process multi-shard transactions (MSTs). In RollShard, each MST is abstracted into a transaction DAG by the Sequencer Shard to ensure the authenticity of the transaction content and the correctness of its execution order. Batched MSTs are dispatched to off-chain executors, each of which simulates transaction logic using a virtual zero-state model integrate with a hierarchical state-delta tree (HSDT). The HSDT employs a Merkle Sum tree to precisely capture batched MSTs’ impact on per-shard account states. Based on the HSDT, the executor generates the zero-knowledge proof to attest the correctness of each shard’s state changes and global value conservation. The resulting net state deltas are then optimistically committed to the relevant shards without cross-shard coordination, reducing intra-shard coordination. We design a game-theoretic incentive mechanism to ensure rational behavior of off-chain executors, showing that honest execution forms a Nash equilibrium under collateral staking. Experimental results based on a prototype deployed in a local area network demonstrate that ROLLSHARDsignificantly outperforms two baseline coordination models proposed in ByShard, namely the Linear and Distributed designs. Specifically, under high workload, RollShard improves throughput by 44.9% and 158%, and reduces cross-shard latency by 38.9% and 42.1%, compared to the Linear and Distributed models, respectively.

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