Papers1 provider · 1 record
May 19, 2026· Research Square
article
Open access

An efficient cross-chain interaction mechanism for large-scale multichain environments

Authors:Xiaohong Deng *Jiayan Liu *Huiwen Liu *Zhigang ChenQiuping LiuYunzhen Zhu

Abstract

Abstract To address the scheduling difficulties, high verification overhead, and insufficient transaction processing efficiency encountered in cross-chain interactions under high-concurrency scenarios, an efficient cross-chain interaction mechanism is proposed. First, a cross-chain interaction framework is constructed, which involves a source chain, a target chain, a smart contract, and an audit chain. The cross-chain request process is uniformly modelled and constrained, realizing the structured and modular organization of the cross-chain process. Second, a hierarchical data preprocessing mechanism based on two-layer K-means clustering is designed. The first layer of clustering homogenizes heterogeneous requests according to their protocol characteristics and transaction structures to eliminate format differences. The second layer of clustering combines dynamic attributes such as transaction priorities, latency sensitivities and timestamps to perform fine-grained division on cross-chain transactions, thereby realizing hierarchical scheduling for disordered requests. Finally, a recursive aggregation-based zero-knowledge proof verification mechanism is constructed. By aggregating the validity proofs of multiple cross-chain transactions into a single recursive proof, the complexity of the cross-chain verification process is reduced from linear to a constant level, significantly reducing the verification overhead and interchain communication latency. A theoretical analysis and experimental results show that the proposed solution can significantly reduce the system overhead in large-scale cross-chain scenarios, improving the cross-chain efficiency rate by 68%-69% relative to that of the existing solutions, and its scalability and efficiency are good in simulated large-scale concurrent scenarios.

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