Narwhal and Tusk: A DAG-based Mempool and Efficient BFT Consensus

We propose separating the task of reliable transaction dissemination from transaction ordering, to enable high-performance Byzantine fault-tolerant quorum-based consensus. We design and evaluate a mempool protocol, Narwhal, specializing in high-throughput reliable dissemination and storage of causal histories of transactions. Narwhal tolerates an asynchronous network and maintains high performance despite failures. Narwhal is designed to easily scale-out using multiple workers at each validator, and we demonstrate that there is no foreseeable limit to the throughput we can achieve. Composing Narwhal with a partially synchronous consensus protocol (Narwhal-HotStuff) yields significantly better throughput even in the presence of faults or intermittent loss of liveness due to asynchrony. However, loss of liveness can result in higher latency. To achieve overall good performance when faults occur we design Tusk, a zero-message overhead asynchronous consensus protocol, to work with Narwhal. We demonstrate its high performance under a variety of configurations and faults. As a summary of results, on a WAN, Narwhal-Hotstuff achieves over 130,000 tx/sec at less than 2-sec latency compared with 1,800 tx/sec at 1-sec latency for Hotstuff. Additional workers increase throughput linearly to 600,000 tx/sec without any latency increase. Tusk achieves 160,000 tx/sec with about 3 seconds latency. Under faults, both protocols maintain high throughput, but Narwhal-HotStuff suffers from increased latency

GeoGauss: Strongly Consistent and Light-Coordinated OLTP for Geo-Replicated SQL Database

Multinational enterprises conduct global business that has a demand for geo-distributed transactional databases. Existing state-of-the-art databases adopt a sharded master-follower replication architecture. However, the single-master serving mode incurs massive cross-region writes from clients, and the sharded architecture requires multiple round-trip acknowledgments (e.g., 2PC) to ensure atomicity for cross-shard transactions. These limitations drive us to seek yet another design choice. In this paper, we propose a strongly consistent OLTP database GeoGauss with full replica multi-master architecture. To efficiently merge the updates from different master nodes, we propose a multi-master OCC that unifies data replication and concurrent transaction processing. By leveraging an epoch-based delta state merge rule and the optimistic asynchronous execution, GeoGauss ensures strong consistency with light-coordinated protocol and allows more concurrency with weak isolation, which are sufficient to meet our needs. Our geo-distributed experimental results show that GeoGauss achieves 7.06X higher throughput and 17.41X lower latency than the state-of-the-art geo-distributed database CockroachDB on the TPC-C benchmark

Proof of Availability & Retrieval in a Modular Blockchain Architecture

This paper explores a modular design architecture aimed at helping blockchains (and other SMR implementation) to scale to a very large number of processes. This comes in contrast to existing monolithic architectures that interleave transaction dissemination, ordering, and execution in a single functionality. To achieve this we first split the monolith to multiple layers which can use existing distributed computing primitives. The exact specification of the data dissemination are formally defined by the Proof of Availability & Retrieval (PoA&R) abstraction. Solutions to the PoA&R problem contain two related sub-protocols: one that ``pushes\u27\u27 information into the network and another that ``pulls\u27\u27 this information. Regarding the latter, there is a dearth of research literature which is rectified in this paper. We present a family of pulling sub-protocols and rigorously analyzing them. Extensive simulations support the theoretical claims of efficiency and robustness in case of a very large number of players. Finally, actual implementation and deployment on a small number of machines (roughly the size of several industrial systems) demonstrates the viability of the architecture\u27s paradigm

Efficient Geo-Distributed Transaction Processing

Distributed deterministic database systems support OLTP workloads over geo-replicated data. Providing these transactions with ACID guarantees requires a delay of multiple wide-area network (WAN) round trips of messaging to totally order transactions globally. This thesis presents Sloth, a geo-replicated database system that can serializably commit transactions after a delay of only a single WAN round trip of messaging. Sloth reduces the cost of determining the total global order for all transactions by leveraging deterministic merging of partial sequences of transactions per geographic region. Using popular workload benchmarks over geo-replicated Azure, this thesis shows that Sloth outperforms state-of-the-art comparison systems to deliver low-latency transaction execution