Large-Scale Causal Data Replication for Stateful Edge Applications

Edge computing is becoming an increasingly popular paradigm, with modern Internet services leveraging hundreds of edge locations to serve their users. However, existing data replication solutions are not designed to operate in this environment, which restricts the edge components of Internet services to operate as read-only caches and entry points for accessing data centers, severely limiting the benefits extracted from the edge. This paper presents Arboreal, a novel distributed data management system for cloud and edge infrastructures that enables stateful edge applications to be deployed with full (read and write) local access to application data, overcoming the limitations of existing solutions. Arboreal's data replication protocol allows it to automatically and dynamically replicate data across edge locations according to application needs, while providing global causal+ consistency. By relying on a hierarchical topology, Arboreal scales to hundreds of edge locations, while recovering from failures in a decentralized and localized manner, without compromising consistency or durability guarantees. Evaluation shows that the scalability of Arboreal heavily outperforms state-of-the-art solutions, while the dynamic replication mechanism allows to effectively support a wide variety of edge scenarios including mobile clients.