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1. Safe Permissionless Consensus

   Pu, Youer (August 2024, Cornell University)

   Nakamoto’s consensus protocol, known for operating in a permissionless model where nodes can join and leave without notice. However, it guarantees agreement only probabilistically. Is this weaker guarantee a necessary concession to the severe demands of supporting a permissionless model? This thesis shows that it is not with the Sandglass and Gorilla Sandglass protocols. Sandglass emerges as the first permissionless consensus algorithm that transcends Nakamoto’s probabilistic limitations by guaranteeing deterministic agreement and termination with probability 1, under general omission failures. It operates under a hybrid synchronous communication model, where, despite the unknown number and dynamic participation of nodes, a majority are consistently correct and synchronously connected. Further building on the framework of Sandglass, Gorilla Sandglass is the first Byzantine fault-tolerant consensus protocol that preserves deterministic agreement and termination with probability 1 within the same synchronous model adopted by Nakamoto. Gorilla addresses the limitations of Sandglass, which only tolerates benign failures, by extending its robustness to include Byzantine failures. We prove the correctness of Gorilla by mapping executions that would violate agreement or termination in Gorilla to executions in Sandglass, where we know such violations are impossible. Establishing termination proves particularly interesting, as the mapping requires reasoning about infinite executions and their probabilities 

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2. Safe Permissionless Consensus

   Pu, Youer; Alvisi, Lorenzo; Eyal, Ittay (October 2022, Leibniz international proceedings in informatics)

   Scheideler, Christian (Ed.)

   Nakamoto’s consensus protocol works in a permissionless model, where nodes can join and leave without notice. However, it guarantees agreement only probabilistically. Is this weaker guarantee a necessary concession to the severe demands of supporting a permissionless model? This paper shows that, at least in a benign failure model, it is not. It presents Sandglass, the first permissionless con- sensus algorithm that guarantees deterministic agreement and termination with probability 1 under general omission failures. Like Nakamoto, Sandglass adopts a hybrid synchronous communication model, where, at all times, a majority of nodes (though their number is unknown) are correct and synchronously connected, and allows nodes to join and leave at any time. 

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3. The Hermes BFT for Blockchains

   https://doi.org/10.1109/TDSC.2021.3114310  

   Jalalzai, Mohammad Mussadiq; Feng, Chen; Busch, Costas; Richard III, Golden; Niu, Jianyu (October 2021, IEEE Transactions on Dependable and Secure Computing)

   The performance of partially synchronous BFT-based consensus protocols is highly dependent on the primary node. All participant nodes in the network are blocked until they receive a proposal from the primary node to begin the consensus process. Therefore, an honest but slack node (with limited bandwidth) can adversely affect the performance when selected as primary. Hermes decreases protocol dependency on the primary node and minimizes transmission delay induced by the slack primary while keeping low message complexity and latency with high scalability. Hermes achieves these performance improvements by relaxing strong BFT agreement (safety) guarantees only for a specific type of Byzantine faults (also called equivocated faults). Interestingly, we show that in Hermes equivocating by a Byzantine primary is expensive and ineffective. Therefore, the safety of Hermes is comparable to the general BFT consensus. We deployed and tested Hermes on 190 Amazon EC2 instances. In these tests, Hermes's performance was comparable to the state-of-the-art BFT protocol for blockchains (when the network size is large) in the absence of slack nodes. Whereas, in the presence of slack nodes, Hermes outperforms the state-of-the-art BFT protocol significantly in terms of throughput and latency. 

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4. LiDO: Linearizable Byzantine Distributed Objects with Refinement-Based Liveness Proofs

   https://doi.org/10.1145/3656423  

   Qiu, Longfei; Kim, Yoonseung; Shin, Ji-Yong; Kim, Jieung; Honoré, Wolf; Shao, Zhong (June 2024, Proceedings of the ACM on Programming Languages)

   Byzantine fault-tolerant state machine replication (SMR) protocols, such as PBFT, HotStuff, and Jolteon, are essential for modern blockchain technologies. However, they are challenging to implement correctly because they have to deal with any unexpected message from Byzantine peers and ensure safety and liveness at all times. Many formal frameworks have been developed to verify the safety of SMR implementations, but there is still a gap in the verification of their liveness. Existing liveness proofs are either limited to the network level or do not cover popular partially synchronous protocols. We introduce LiDO, a consensus model that enables the verification of both safety and liveness of implementations through refinement. We observe that current consensus models cannot handle liveness because they do not include a pacemaker state. We show that by adding a pacemaker state to the LiDO model, we can express the liveness properties of SMR protocols as a few safety properties that can be easily verified by refinement proofs. Based on our LiDO model, we provide mechanized safety and liveness proofs for both unpipelined and pipelined Jolteon in Coq. This is the first mechanized liveness proof for a byzantine consensus protocol with non-trivial optimizations such as pipelining. 

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5. Blockchains and Databases: Opportunities and Challenges for the Permissioned and the Permissionless

   https://doi.org/10.1007/978-3-030-54832-2_1  

   Agrawal, D.; El Abbadi, A.; Amiri, M.J.; Maiyya, S.; Zakhary, V. (August 2020, Advances in Databases and Information Systems)

   Darmont, J; Novikov, B.; Wrembel, R. (Ed.)

   Bitcoin [12] is a successful and interesting example of a global scale peer-to-peer cryptocurrency that integrates many techniques and protocols from cryptography, distributed systems, and databases. The main underlying data structure is blockchain, a scalable fully replicated structure that is shared among all participants and guarantees a consistent view of all user transactions by all participants in the system. In a blockchain, nodes agree on their shared states across a large network of untrusted participants. Although originally devised for cryptocurrencies, recent systems exploit its many unique features such as transparency, provenance, fault tolerance, and authenticity to support a wide range of distributed applications. Bitcoin and other cryptocurrencies use permissionless blockchains. In a permissionless blockchain, the network is public, and anyone can participate without a specific identity. Many other distributed applications, such as supply chain management and healthcare, are deployed on permissioned blockchains consisting of a set of known, identified nodes that still might not fully trust each other. This paper illustrates some of the main challenges and opportunities from a database perspective in the many novel and interesting application domains of blockchains. These opportunities are illustrated using various examples from recent research in both permissionless and permissioned blockchains. Two main themes unite the various examples: (1) the important role of distribution and consensus in managing large scale systems and (2) the need to tolerate malicious failures. The advent of cloud computing and large data centers shifted large scale data management infrastructures from centralized databases to distributed systems. One of the main challenges in designing distributed systems is the need for fault-tolerance. Cloud-based systems typically assume trusted infrastructures, since data centers are owned by the enterprises managing the data, and hence the design typically only assumes and tolerates crash failures. The advent of blockchain and the underlying premise that copies of the blockchain are distributed among untrusted entities has shifted the focus of fault-tolerance from tolerating crash failures to tolerating malicious failures. These interesting and challenging settings pose great opportunities for database researchers. 

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