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Eventual consistency is a consistency model that favors liveness over safety. It is often used in large-scale distributed systems where models ensuring a stronger safety incur performance that are too low to be deemed practical. Eventual consistency tends to be uniformly applied within a system, but we argue a demand exists for differentiated eventual consistency, e.g. in blockchain systems. We propose UPS to address this demand. UPS is a novel consistency mechanism that works in pair with our novel two-phase epidemic broadcast protocol GPS to offer differentiated eventual consistency and delivery speed. We propose two complementary analyses of the broadcast protocol: a continuous analysis and a discrete analysis based on compartmental models used in epidemiology. Additionally, we propose the formal definition of a scalable consistency metric to measure the consistency trade-off at runtime. We evaluate UPS in two simulated worldwide settings: a one-million-node network and a network emulating that of the Ethereum blockchain. In both settings, UPS reduces inconsistencies experienced by a majority of the nodes and reduces the average message latency for the remaining nodes.
Rachid Guerraoui, Gauthier Jérôme Timothée Voron, Vincent Gramoli, Andrei Lebedev
Bryan Alexander Ford, Verónica del Carmen Estrada Galiñanes, Louis-Henri Manuel Jakob Merino, Haoqian Zhang, Mahsa Bastankhah
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