因果一致部分复制的全局镇定

Zhuolun Xiang, N. Vaidya
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引用次数: 11

摘要

因果一致性分布式存储系统由于具有提供高吞吐量的潜力而受到了极大的关注。全局稳定是为了在分布式多版本键值存储系统中实现因果一致性而建立的一种技术,以前的作品如GentleRain[6]和Cure[1]采用了这种技术。但是,以前具有全局稳定性的设计假设了完全复制,其中数据集被分割成分区,每个分区在所有数据中心复制,并且每个客户机被限制只能访问一个数据中心内的服务器。在本文中,我们提出了一个全局稳定的理论框架,以支持具有因果一致性的通用部分复制,其中每个服务器可以存储任意子集的数据,并且每个客户端允许与服务器的任何子集通信并在它们之间进行迁移,而不会产生额外的延迟。我们提出了一种算法,该算法通过通用部分复制实现分布式多版本键值存储的因果一致性,并且我们的算法在远程更新可见性延迟方面是最佳的,即在通用部分复制下,来自远程服务器的更新对客户端的可见速度有多快。最后给出了算法性能与已有算法的对比仿真结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Global Stabilization for Causally Consistent Partial Replication
Causally consistent distributed storage systems have received significant attention due to the potential for providing high throughput. Global stabilization is a technique established for achieving causal consistency in distributed multi-version key-value store systems, adopted by previous works such as GentleRain [6] and Cure [1]. However, previous designs with global stabilization assume full replication, where the set of the data is split into partitions with each partition replicated at all data centers, and each client is restricted to access servers within only one data center. In this paper, we propose a theoretical framework of global stabilization to support general partial replication with causal consistency, where each server can store an arbitrary subset of the data, and each client is allowed to communicate with any subset of the servers and migrate among them without extra delays. We propose an algorithm that implements causal consistency for distributed multi-version key-value stores with general partial replication, and our algorithm is optimal in terms of the remote update visibility latency, i.e. how fast update from a remote server is visible to the client, under general partial replication. Simulation results on the performance of our algorithm compared to the previous work are also provided.
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