论文标题
历史数据驱动的网络分布共识
History Data Driven Distributed Consensus in Networks
论文作者
论文摘要
分布式共识协议中的权重关联量化了代理商对网络中其邻居的信任。在这种网络系统中，一个重要的问题是估计相邻代理之间信任的不确定性，再加上由于错误地将错误量的信任与不同的邻近代理联系起来而造成的损失。我们引入了一种概率方法，该方法使用网络中收集的历史数据来确定每个代理之间的信任水平。具体而言，使用邻居之间共享数据的有限历史记录，我们获得了一种配置，该配置代表了每个相邻代理人的可信度的置信度估计。最后，我们提出了一个历史数据驱动的（HDD）分布式共识协议，该协议将计算的配置数据转化为在共识更新中使用的权重。在分布式共识设置的背景下，使用历史数据的方法标志着我们论文的新贡献。
The association of weights in a distributed consensus protocol quantify the trust that an agent has on its neighbors in a network. An important problem in such networked systems is the uncertainty in the estimation of trust between neighboring agents, coupled with the losses arising from mistakenly associating wrong amounts of trust with different neighboring agents. We introduce a probabilistic approach which uses the historical data collected in the network, to determine the level of trust between each agent. Specifically, using the finite history of the shared data between neighbors, we obtain a configuration which represents the confidence estimate of every neighboring agent's trustworthiness. Finally, we propose a History-Data-Driven (HDD) distributed consensus protocol which translates the computed configuration data into weights to be used in the consensus update. The approach using the historical data in the context of a distributed consensus setting marks the novel contribution of our paper.
