Abstract
The consortium blockchain based on on-chain and off-chain data storage methods has shared cross-department business data widely. Existing research focuses on using index and other technologies to optimize a single query in the consortium blockchain, needing proper planning and scheduling for multi-user data access on-chain and off-chain. This paper fully considers the cross-department collaborative query requirements of the consortium blockchain and studies the reasonable allocation of nodes on and off the chain for multiple query tasks. The optimization model for cooperative query on and off the chain and the corresponding solution method is proposed. Firstly, the collaborative query optimization problem of on-chain and off-chain is modeled, considering the query processing capabilities of on-chain and off-chain nodes, and minimizes the query time as the optimization goal. Secondly, based on Coyote Optimization Algorithm (COA) and Genetic Algorithm (GA), a Hybrid Coyote Optimization Algorithm HCOA-GA (Hybrid COA-GA) is proposed. The experimental results show that the algorithm proposed can obtain the multi-user collaborative query optimization scheme on and off the chain and has better query time and convergence speed performance than other algorithms.
This work is supported by the Key Science and Technology Program of the Open Competition Mechanism to Select the Best Candidates of Liaoning Province, China (Grant No.2021JH1/10400010).
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Wang, J., Li, Y., Tan, A., Gong, Z., Wang, Y. (2023). Multi-User On-Chain and Off-Chain Collaborative Query Optimization Based on Consortium Blockchain. In: Yuan, L., Yang, S., Li, R., Kanoulas, E., Zhao, X. (eds) Web Information Systems and Applications. WISA 2023. Lecture Notes in Computer Science, vol 14094. Springer, Singapore. https://doi.org/10.1007/978-981-99-6222-8_40
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