SP-DEWOA: An Evolutionary Distributed Witness Node Election Method for Delegated Proof of Stake

Delegated Proof of Stake (DPoS) is a widely utilized consensus protocol in blockchain-based Internet of Things (IoT) systems. We propose a heuristic algorithm-based accounting rights allocation method, also referred to as the witness election method, which aims to address the challenges in DPoS. The challenges associated with selected witness nodes that do not reflecting majority stakeholder preferences and susceptibility to manipulation of the vote. This method employs the Kendall’s rank correlation as the fitness function to optimize the arrangement of the top-k producers, thereby maximizing stakeholder preferences. We propose a novel heuristic algorithm, termed SP-DEWOA, which combines the differential evolution algorithm and whale optimization with piecewise chaotic mapping to maximize permutation similarity, i.e., stakeholder preferences. To further improve the efficiency of SP-DEWOA, we parallelize SP-DEWOA based on the Spark-based parallelization design. Experimental results demonstrate that the witness nodes selected through SP-DEWOA are consistent with the preferences of the majority of stakeholders. Furthermore, SP-DEWOA has been proven to have high scalability and resilience against vote manipulation.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-10-08
DOI
https://doi.org/10.1109/jiot.2024.3476248
Citations
3
Primary Topic
Privacy-Preserving Technologies in Data
Type
article
Field-Weighted Citation Impact
1.04
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article

SP-DEWOA: An Evolutionary Distributed Witness Node Election Method for Delegated Proof of Stake

Jinze Du, Hao Lin
3 citations
IEEE Internet of Things Journal
Privacy-Preserving Technologies in Data
1.04
article

SP-DEWOA: An Evolutionary Distributed Witness Node Election Method for Delegated Proof of Stake

Jinze Du, Hao Lin
article en
3 citations

Abstract

Delegated Proof of Stake (DPoS) is a widely utilized consensus protocol in blockchain-based Internet of Things (IoT) systems. We propose a heuristic algorithm-based accounting rights allocation method, also referred to as the witness election method, which aims to address the challenges in DPoS. The challenges associated with selected witness nodes that do not reflecting majority stakeholder preferences and susceptibility to manipulation of the vote. This method employs the Kendall’s rank correlation as the fitness function to optimize the arrangement of the top-k producers, thereby maximizing stakeholder preferences. We propose a novel heuristic algorithm, termed SP-DEWOA, which combines the differential evolution algorithm and whale optimization with piecewise chaotic mapping to maximize permutation similarity, i.e., stakeholder preferences. To further improve the efficiency of SP-DEWOA, we parallelize SP-DEWOA based on the Spark-based parallelization design. Experimental results demonstrate that the witness nodes selected through SP-DEWOA are consistent with the preferences of the majority of stakeholders. Furthermore, SP-DEWOA has been proven to have high scalability and resilience against vote manipulation.

IEEE Internet of Things JournalVol. 12(3)
Tianjin University of Technology (CN)
Openalex Percentile: Top 19%
Privacy-Preserving Technologies in Data
1.04
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