In distributed systems, a group of $\textit{learners}$ achieve $\textit{consensus}$ when, by observing the output of some $\textit{acceptors}$, they all arrive at the same value. Consensus is crucial for ordering transactions in failure-tolerant systems. Traditional consensus algorithms are homogeneous in three ways: - all learners are treated equally, - all acceptors are treated equally, and - all failures are treated equally. These assumptions, however, are unsuitable for cross-domain applications, including blockchains, where not all acceptors are equally trustworthy, and not all learners have the same assumptions and priorities. We present the first consensus algorithm to be heterogeneous in all three respects. Learners set their own mixed failure tolerances over differently trusted sets of acceptors. We express these assumptions in a novel $\textit{Learner Graph}$, and demonstrate sufficient conditions for consensus. We present $\textit{Heterogeneous Paxos}$: an extension of Byzantine Paxos. Heterogeneous Paxos achieves consensus for any viable Learner Graph in best-case three message sends, which is optimal. We present a proof-of-concept implementation, and demonstrate how tailoring for heterogeneous scenarios can save resources and latency.

中文翻译：

---

异构 Paxos：技术报告

在分布式系统中，一组 $\textit{learners}$ 实现 $\textit{consensus}$ 当，通过观察一些 $\textit{acceptors}$ 的输出，它们都达到相同的值。共识对于在容错系统中订购交易至关重要。传统的共识算法在三个方面是同质的： - 所有学习者都被平等对待， - 所有接受者都被平等对待，以及 - 所有失败都被平等对待。然而，这些假设不适用于跨域应用程序，包括区块链，其中并非所有的接受者都同样值得信赖，并且并非所有的学习者都具有相同的假设和优先级。我们提出了第一个在所有三个方面都是异构的共识算法。学习者在不同的受信任的接受者集上设置自己的混合故障容限。我们在一个新的 $\textit{Learner Graph}$ 中表达了这些假设，并证明了达成共识的充分条件。我们提出 $\textit{Heterogeneous Paxos}$：拜占庭 Paxos 的扩展。异构 Paxos 在最好的三种消息发送中为任何可行的学习者图达成共识，这是最优的。我们提出了一个概念验证实现，并展示了针对异构场景的定制如何可以节省资源和延迟。