Ethereum is the dominant blockchain ecosystem capable of executing Turing-complete smart contracts. Rollups gained significant traction as the primary layer 2 (L2) solution meant to bring horizontal scalability to the main Ethereum network (L1). A core component of any rollup is the sequencer, which creates new L2 blocks to be submitted in rollup batches to L1. In most of the current rollup architectures, this component is centralised. As a result, these designs are prone to inconspicuous censorship practices by the sequencer. Trusted execution environments (TEEs) can guarantee the integrity of various sequencer components, which is instrumental in addressing censorship. However, the reaction of the system design to censorship attempts depends on where a TEE is integrated and which components it protects. In particular, this reaction is limited in the case of a monolithic TEE-protected sequencer design. Proposer-Builder Separation (PBS) is a non-monolithic paradigm adopted on L1, which separates the production of blocks from proposing them for inclusion in the blockchain. Recently, PBS has been considered for integration with L2 sequencers, with an impact on alleviating censorship. In this paper, we explore the design space of TEE-integrating PBS and non-PBS sequencer variants. First, we introduce a formal framework for the censorship actions that captures the specificity of the L2 sequencer. Then, we analyse to what extent the different designs address these censorship actions. Our main contribution is a novel design variation that allows for a precise observation of censored transactions. In the presence of TEEs, in a PBS setting, we demonstrate this precise observability, which is necessary to enable resilience to censorship.
This paper studies distributed-computing tasks through the lens of space complexity in the read/write wait-free model, defined as the number of multi-reader-multi-writer atomic read/write registers needed to solve a task using a wait-free algorithm. Surprisingly, even though the read/write wait-free model is at the foundation of distributed computing, previous work on space complexity has focused on synchronization primitives stronger than read/write registers or on weaker progress conditions. The paper reveals that the read/write wait-free model offers a rich space-complexity landscape: (1) assuming non-anonymous processes, it shows that there is an infinite hierarchy of tasks of increasing space complexity; (2) it shows that space complexity separates anonymous from non-anonymous memory; (3) regardless of process or register anonymity, it exhibits a task of space complexity two, which is the minimal non-trivial space complexity; (4) finally, it shows that subcases of the adopt-commit task have different space complexity in non-anonymous memory under bounded wait-freedom.
To achieve fast recovery from link failures, most modern communication networks feature fully decentralized fast re-routing mechanisms. These re-routing mechanisms rely on pre-installed static re-routing rules at the nodes (the routers), which depend only on local failure information, namely on the failed links incident to the node. Ideally, a network is perfectly resilient: the re-routing rules ensure that packets are always successfully routed to their destinations as long as the source and the destination are still physically connected in the underlying network after the failures. Unfortunately, there are examples where achieving perfect resilience is not possible. Surprisingly, only very little is known about the algorithmic aspect of when and how perfect resilience can be achieved. We investigate the computational complexity of analyzing such local fast re-routing mechanisms. Our main result is a negative one: we show that even checking whether a given set of static re-routing rules ensures perfect resilience is coNP-complete. Additionally, we investigate other fundamental variations of the problem. In particular, we show that our coNP-completeness proof also applies to scenarios where the re-routing rules have specific patterns (known as skipping in the literature). On the positive side, for scenarios where nodes do not have information about the link from which a packet arrived (the so-called in-port), we present a linear-time algorithm to realize perfect resilience whenever possible (which we show can also be determined in linear time).
The class of extension-based proofs encompasses traditional valency arguments. It has been shown that they are insufficient to establish the impossibility of (n - 1)-set agreement among n >= 3 processes in an asynchronous system with crash failures. We generalize this definition to k-exhaustive extension-based proofs, in which a prover can learn the maximum length of all executions involving a set of at most k processes from a specified configuration (which may be infinite). An upper bound on the length of these executions enables the prover to determine the outputs of all these executions. When k = n, this enables the prover to perform an exhaustive search of all reachable configurations, so it knows everything about the protocol. On the other hand, extension based proofs are as powerful as 1-exhaustive extension-based proofs. For any task with no deterministic, wait-free solution among n >= 2 processes, we show that there is an (n- 1)-exhaustive extension-based proof of its impossibility. This is done using a new characterization of such tasks. In contrast, we prove that for 1 <= k <= n- 2, there is no k-exhaustive extension-based proof of the impossibility of ( n - 1)-set agreement.
As shown by Reliable Broadcast and Consensus, cooperation among a set of independent computing entities (sequential processes) is crucial in fault-tolerant distributed computing. Considering nprocess asynchronous message-passing systems where some processes may be Byzantine, this paper introduces a novel cooperation abstraction, Contention-Aware Cooperation (CAC). While Reliable Broadcast is a one-to- n cooperation abstraction and Consensus is an n-to- n cooperation abstraction, CAC is a d-to- n cooperation abstraction where d (1 <= d <= n) varies with each run and remains unknown to the processes. Correct processes accept the same set of l pairs v, i ( v is the value proposed by p(i)) from the d proposer processes, where 1 <= l <= d and (as d) l remains unknown to the processes (except in specific cases). Those l values are accepted one at a time, potentially in different orders at each process. In addition, CAC provides each process with an imperfect oracle that provides insights into the values that they may accept in the future. Interestingly, the CAC abstraction is particularly efficient in favorable circumstances, when the oracle becomes accurate, which processes can detect. To illustrate its practical utility, the paper details two applications leveraging CAC: a fast consensus implementation optimized for low contention (named Cascading Consensus), and a novel naming problem that can be solved under full asynchrony. All algorithms presented require signatures.
