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<p>As the foundation of distributed systems, consensus mechanisms play a crucial role in ensuring the proper operation of the system. In a distributed network composed of trusted peer nodes, nodes may need to perform operations on random Boolean values (0 or 1) during their execution. To address this, this paper, inspired by Paxos, Raft, and their derivative algorithms, proposes a random Boolean consensus algorithm based on the principle of the Probabilistic Propagation Model. In each consensus round, a Boolean value is selected with a smaller probability in the first round of communication, and the final decision is made with a larger probability in the second round, ensuring that the probabilities of the system obtaining 0 or 1 are approximately equal. The running time is further reduced by minimizing the participation of nodes. Experimental results show that this method enables nodes in the system to quickly reach a consensus on a random Boolean value, and as the number of nodes increases, the savings in system overhead become more apparent.</p>

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PTSC: an efficient random boolean consensus algorithm for distributed systems with the probabilistic propagation model

  • 期刊论文

  • 发表日期：

    2025年5月22日

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  • Yuke Cao,
  • Kun She,
  • Yuxuan Xiao,
  • Yongyue Wu,
  • Yuntao Ren,
  • Ruidong Chen

摘要

As the foundation of distributed systems, consensus mechanisms play a crucial role in ensuring the proper operation of the system. In a distributed network composed of trusted peer nodes, nodes may need to perform operations on random Boolean values (0 or 1) during their execution. To address this, this paper, inspired by Paxos, Raft, and their derivative algorithms, proposes a random Boolean consensus algorithm based on the principle of the Probabilistic Propagation Model. In each consensus round, a Boolean value is selected with a smaller probability in the first round of communication, and the final decision is made with a larger probability in the second round, ensuring that the probabilities of the system obtaining 0 or 1 are approximately equal. The running time is further reduced by minimizing the participation of nodes. Experimental results show that this method enables nodes in the system to quickly reach a consensus on a random Boolean value, and as the number of nodes increases, the savings in system overhead become more apparent.