Fault-Tolerant Consensus in Unknown and Anonymous Networks

This paper investigates under which conditions information can be reliably shared and consensus can be solved in unknown and anonymous message-passing networks that suffer from crash-failures. We provide algorithms to emulate registers and solve consensus under different synchrony assumptions. For this, we introduce a novel pseudo leader-election approach which allows a leader-based consensus implementation without breaking symmetry

QuePaxa: Escaping the tyranny of timeouts in consensus

Leader-based consensus algorithms are fast and efficient under normal conditions, but lack robustness to adverse conditions due to their reliance on timeouts for liveness. We present QuePaxa, the first protocol offering state-of-the-art normal-case efficiency without depending on timeouts. QuePaxa uses a novel randomized asynchronous consensus core to tolerate adverse conditions such as denial-of-service (DoS) attacks, while a one-round-trip fast path preserves the normal-case efficiency of Multi-Paxos or Raft. By allowing simultaneous proposers without destructive interference, and using short hedging delays instead of conservative timeouts to limit redundant effort, QuePaxa permits rapid recovery after leader failure without risking costly view changes due to false timeouts. By treating leader choice and hedging delay as a multi-armed-bandit optimization, QuePaxa achieves responsiveness to prevalent conditions, and can choose the best leader even if the current one has not failed. Experiments with a prototype confirm that QuePaxa achieves normal-case LAN and WAN performance of 584k and 250k cmd/sec in throughput, respectively, comparable to Multi-Paxos. Under conditions such as DoS attacks, misconfigurations, or slow leaders that severely impact existing protocols, we find that QuePaxa remains live with median latency under 380ms in WAN experiments

Brief Announcement: Ordered Reliable Broadcast and Fast Ordered Byzantine Consensus for Cryptocurrency

The problem of transaction reordering in blockchains, also known as the blockchain anomaly [Christopher Natoli and Vincent Gramoli, 2016], can lead to fairness limitations [Kelkar et al., 2020] and front-running activities [Philip Daian et al., 2020] in cryptocurrency. To cope with this problem despite f < n/3 byzantine processes, Zhang et al. [Zhang et al., 2020] have introduced the ordering linearizability property ensuring that if two transactions or commands are perceived by all correct processes in the same order, then they are executed in this order. They proposed a generic distributed protocol that first orders commands and then runs a leader-based consensus protocol to agree on these orders, hence requiring at least 11 message delays. In this paper, we parallelize the ordering with the execution of the consensus to require only 6 message delays. For the ordering, we introduce the ordered reliable broadcast primitive suitable for broadcast-based cryptocurrencies (e.g., [Daniel Collins et al., 2020]). For the agreement, we build upon the DBFT leaderless consensus protocol [Tyler Crain et al., 2018] that was recently formally verified [Bertrand et al., 2021]. The combination is thus suitable to ensure ordering linearizability in consensus-based cryptocurrencies (e.g., [Tyler Crain et al., 2021])

Wait-Freedom with Advice

We motivate and propose a new way of thinking about failure detectors which allows us to define, quite surprisingly, what it means to solve a distributed task \emph{wait-free} \emph{using a failure detector}. In our model, the system is composed of \emph{computation} processes that obtain inputs and are supposed to output in a finite number of steps and \emph{synchronization} processes that are subject to failures and can query a failure detector. We assume that, under the condition that \emph{correct} synchronization processes take sufficiently many steps, they provide the computation processes with enough \emph{advice} to solve the given task wait-free: every computation process outputs in a finite number of its own steps, regardless of the behavior of other computation processes. Every task can thus be characterized by the \emph{weakest} failure detector that allows for solving it, and we show that every such failure detector captures a form of set agreement. We then obtain a complete classification of tasks, including ones that evaded comprehensible characterization so far, such as renaming or weak symmetry breaking