Consistent replication of data among distributed processes -- a task involving the well-known consensus problem -- is notoriously expensive and hard to scale, affecting especially datacenter services with stringent performance requirements. To mitigate this problem, we introduce scalable replication in-hardware ( scarHW ): a network card design that improves throughput and latency of consistent replication even when increasing the number of replicas, whereas current systems operate at a small scale or with relaxed consistency guarantees. At the heart of scarHW is our novel POPUC consensus algorithm, implemented in an FPGA smartNIC to take full advantage of the"mostly synchronous"behavior of programmable network devices in the datacenter. Unlike widely-adopted"mostly asynchronous"coordination protocols such as Paxos or leaderless alternatives, POPUC implements a generalized variant of consensus dubbed collaborative consensus which allows for several simultaneous decisions, achieving great scalability without compromising availability. POPUC preserves safety guarantees in the presence of process crash-stop and message send/receive omission failures (capturing incidental asynchrony) and has been formally specified and verified in TLA+. Our FPGA prototype improves throughput and latency of widely-used services Redis and Zookeeper by up to two orders of magnitude compared to the state of the art. scarHW-based services also achieve zero downtime upon failure of a minority of replicas, offering a highly-robust, wire-speed, scalable replication system.
Fast consensus protocols, such as CURP-Q and NOPaxos, have coupled objectives of reducing latency and tolerating faults, but doing so incurs considerable processing overhead and/or necessitates complex changes to existing architectures. Our insight is that when no adverse execution conditions (including operation confl...
Yan Chen, Xinyi Yu, Shengyun Liu et al.· Conference on Applications,...· 0 citations
Modern datacenters exhibit different timing properties across the network fabric and the host software stack: the former offers bounded-delay delivery and precise clock synchronization, whereas the latter provides greater flexibility but substantially greater timing variability. This substrate-level separation matches...
Yuke Ma, Paolo Costa, Yiting Xia· Proceedings of the 17th ACM...· 0 citations
Large-scale data management systems rely on fault-tolerant protocols to ensure availability and consistency in the presence of node failures. However, standard protocols require majority quorums in every phase, making them impractical in environments with frequent failures, such as IoT networks. This paper presents O...
Kevin Dharmawan, Prajwal Annigeri, Mohammad Javad Amiri· Proceedings of the VLDB Endo...· 0 citations
Scalability remains a major challenge for Byzantine fault tolerance (BFT) systems, whose throughput is often limited by sequential transaction processing at each node. Prior work has attempted to address this challenge by full sharding or by replacing total ordering with serializable concurrent execution, but these app...
Guang-Da Sun, Jialin Li· Proceedings of the 17th ACM...· 0 citations
Strongly consistent geo-replication often relies on fast paths to reduce latency in the common case of no failures or contention. Existing fast-path schemes, however, are ad hoc and restrictive: each corresponds to a point in a broad design space shaped by network topology, workload, and latency objective, so no single...
Clément Burgelin, Antoine Murat, G. Sela et al.· 0 citations
Data replication is a fundamental mechanism in distributed database systems, supporting fault
tolerance, availability, and reliable data access across networked nodes. Cockroach DB is a cloud
native, open-source distributed SQL database that relies on replication and consensus protocols
to maintain consistency and re...
Famvie Egboson· International Journal of Com...· 0 citations
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