Global Stabilization for Causally Consistent Partial Replication
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Causally consistent distributed storage systems have received significant attention recently due to the potential for providing high throughput and causality guarantees. Global stabilization is a technique established for ensuring causal consistency in distributed storage systems, adopted by the previous work such as GentleRain Du2014GentleRainCA and Cure akkoorath2016cure. It allows the client to read consistently without explicit dependency checking, thus enables low latency and high throughput. However, most of the previous designs assume full replication, where each data center stores a full copy of data. In this paper, we extend global stabilization to general partial replication, where each server can store an arbitrary subset of the data, and the clients are allowed to communicate with any subset of the servers. We propose an algorithm that implements causally consistency partially replicated distributed storage using global stabilization. We prove the correctness of our algorithm and provide an efficient implementation. We also discuss several optimizations that can improve the performance of our algorithm.
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