In-Network Leaderless Replication for Distributed Data Stores

Gyuyeong Kim, Wonjun Lee

Research output: Contribution to journalConference articlepeer-review

Abstract

Leaderless replication allows any replica to handle any type of request to achieve read scalability and high availability for distributed data stores. However, this entails burdensome coordination overhead of replication protocols, degrading write throughput. In addition, the data store still requires coordination for membership changes, making it hard to resolve server failures quickly. To this end, we present NetLR, a replicated data store architecture that supports high performance, fault tolerance, and linearizability simultaneously. The key idea of NetLR is moving the entire replication functions into the network by leveraging the switch as an on-path in-network replication orchestrator. Specifically, NetLR performs consistency-aware read scheduling, high-performance write coordination, and active fault adaptation in the network switch. Our in-network replication eliminates inter-replica coordination for writes and membership changes, providing high write performance and fast failure handling. NetLR can be implemented using programmable switches at a line rate with only 5.68% of additional memory usage. We implement a prototype of NetLR on an Intel Tofino switch and conduct extensive testbed experiments. Our evaluation results show that NetLR is the only solution that achieves high throughput and low latency and is robust to server failures.

Original languageEnglish
Pages (from-to)1337-1349
Number of pages13
JournalContemporary Mathematics
Volume15
Issue number7
DOIs
Publication statusPublished - 2022
Event48th International Conference on Very Large Data Bases, VLDB 2022 - Sydney, Australia
Duration: 2022 Sep 52022 Sep 9

ASJC Scopus subject areas

  • Mathematics(all)

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