A Blockchain-Based Framework for Supervision of Livelihood Issues: Proof of Concept With Optimized Consensus

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Abstract

Supervision of Livelihood Issues (SLI) refers to the supervision and participation of the general public in government actions and public affairs, with a particular focus on issues closely related to people's lives. However, current regulatory systems often suffers from information imbalances, low authenticity, and credibility. To address these challenges, this study proposes a blockchain-based SLI framework that leverages the decentralized, tamper-proof, traceable, and transparent nature of blockchain technology to provide a reliable platform for SLI. Furthermore, we designed an information data structure on the blockchain and presented the information flow process. We developed smart contracts that utilize automation capability to automatically aggregate, analyze, and publish warnings based on on-chain data, enabling the evaluation of relevant departments' performance. Moreover, in the context of SLI applications, we propose an optimized consensus algorithm called the SLI-PBFT. This algorithm is based on the PBFT consensus protocol and incorporates dynamic scalability mechanisms, scoring models, and simplified consistency protocols to enhance the consensus efficiency of SLI applications. Finally, the experiments were conducted. We developed an SLI prototype system and compared and analyzed the performance of SLI-PBFT with other PBFT-based consensus algorithms within the SLI prototype system. The experimental results demonstrated the feasibility of the SLI framework. Moreover, SLI-PBFT exhibits significant improvements in throughput and reduced latency compared to other algorithms in the context of SLI applications. In addition, they possess strong fault tolerances and security capabilities. This study provides theoretical and practical guidance for the SLI in real-world scenarios.

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Xu, J., Hua, C., & Zhang, Y. (2023). A Blockchain-Based Framework for Supervision of Livelihood Issues: Proof of Concept With Optimized Consensus. IEEE Access, 11, 73414–73434. https://doi.org/10.1109/ACCESS.2023.3295696

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