RotorcRaft: Scalable Follower-Driven Raft on RDMA

Xuecheng Qi, Huiqi Hu, Xing Wei, Aoying Zhou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

State machine replication plays a fundamental role in meeting both the scalability and the fault-tolerance requirement in cloud services. However, the single-point leader is easy to become a bottleneck of scalability because it needs to handle all read and write requests and independently replicate logs in order for all followers. Moreover, machine resources are shared through cloud services where the scale-up of the leader is very expensive. In this paper, we propose a variant of Raft protocol using RDMA named RotorcRaft to significantly offload burden from the leader to followers to relieve the single-point bottleneck. First, RotorcRaft assigns a follower-driven log replication mechanism that exploits hybrid RDMA primitives to relieve part of the burden of leader to followers in log replication. Then, RotorcRaft proposes a quorum follower read that enables followers to handle read requests without the involvement of the leader. Experimental results demonstrate that RotorcRaft has excellent scalability and up to 1.4x higher throughput with 84% latency compared against the state-of-the-art work.

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications - 27th International Conference, DASFAA 2022, Proceedings
EditorsArnab Bhattacharya, Janice Lee Mong Li, Divyakant Agrawal, P. Krishna Reddy, Mukesh Mohania, Anirban Mondal, Vikram Goyal, Rage Uday Kiran
PublisherSpringer Science and Business Media Deutschland GmbH
Pages293-308
Number of pages16
ISBN (Print)9783031001222
DOIs
StatePublished - 2022
Event27th International Conference on Database Systems for Advanced Applications, DASFAA 2022 - Virtual, Online
Duration: 11 Apr 202214 Apr 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13245 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference27th International Conference on Database Systems for Advanced Applications, DASFAA 2022
CityVirtual, Online
Period11/04/2214/04/22

Keywords

  • Follower-driven
  • RDMA
  • Raft

Fingerprint

Dive into the research topics of 'RotorcRaft: Scalable Follower-Driven Raft on RDMA'. Together they form a unique fingerprint.

Cite this