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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.
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Bryan Alexander Ford, Verónica del Carmen Estrada Galiñanes, Louis-Henri Manuel Jakob Merino, Haoqian Zhang, Mahsa Bastankhah
Rachid Guerraoui, Gauthier Jérôme Timothée Voron, Vincent Gramoli, Andrei Lebedev