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State Machine Replication Is More Expensive Than Consensus

Authors Karolos Antoniadis, Rachid Guerraoui, Dahlia Malkhi, Dragos-Adrian Seredinschi

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Karolos Antoniadis
  • EPFL, Lausanne, Switzerland
Rachid Guerraoui
  • EPFL, Lausanne, Switzerland
Dahlia Malkhi
  • VMware Research, Palo Alto, USA
Dragos-Adrian Seredinschi
  • EPFL, Lausanne, Switzerland

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Karolos Antoniadis, Rachid Guerraoui, Dahlia Malkhi, and Dragos-Adrian Seredinschi. State Machine Replication Is More Expensive Than Consensus. In 32nd International Symposium on Distributed Computing (DISC 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 121, pp. 7:1-7:18, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)


Consensus and State Machine Replication (SMR) are generally considered to be equivalent problems. In certain system models, indeed, the two problems are computationally equivalent: any solution to the former problem leads to a solution to the latter, and vice versa. In this paper, we study the relation between consensus and SMR from a complexity perspective. We find that, surprisingly, completing an SMR command can be more expensive than solving a consensus instance. Specifically, given a synchronous system model where every instance of consensus always terminates in constant time, completing an SMR command does not necessarily terminate in constant time. This result naturally extends to partially synchronous models. Besides theoretical interest, our result also corresponds to practical phenomena we identify empirically. We experiment with two well-known SMR implementations (Multi-Paxos and Raft) and show that, indeed, SMR is more expensive than consensus in practice. One important implication of our result is that - even under synchrony conditions - no SMR algorithm can ensure bounded response times.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Distributed algorithms
  • Consensus
  • State machine replication
  • Synchronous model


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