Brief Announcement: Towards Energy-Efficient Distributed Agreement

We study fault-tolerant consensus in a variant of the synchronous message passing model, where, in each round, every node can choose to be awake or asleep. This is known as the sleeping model (Chatterjee, Gmyr, Pandurangan PODC 2020) and defines the awake complexity (also called energy complexity), which measures the maximum number of rounds that any node is awake throughout the execution. Only awake nodes can send and receive messages in a given round and all messages sent to sleeping nodes are lost. We present new deterministic consensus algorithms that tolerate up to f < n crash failures, where n is the number of nodes. Our algorithms match the optimal time complexity lower bound of f + 1 rounds. For multi-value consensus, where the input values are chosen from some possibly large set, we achieve an energy complexity of [EQUATION] rounds, whereas for binary consensus, we show that [EQUATION] rounds are possible.

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Publication Details

Published
2025-06-13
DOI
https://doi.org/10.1145/3732772.3733554
Primary Topic
Distributed systems and fault tolerance
Type
article
Field-Weighted Citation Impact
0.00

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article

Brief Announcement: Towards Energy-Efficient Distributed Agreement

Peter Robinson, Hugo Mirault
Distributed systems and fault tolerance
article

Brief Announcement: Towards Energy-Efficient Distributed Agreement

Peter Robinson, Hugo Mirault
article en

Abstract

We study fault-tolerant consensus in a variant of the synchronous message passing model, where, in each round, every node can choose to be awake or asleep. This is known as the sleeping model (Chatterjee, Gmyr, Pandurangan PODC 2020) and defines the awake complexity (also called energy complexity), which measures the maximum number of rounds that any node is awake throughout the execution. Only awake nodes can send and receive messages in a given round and all messages sent to sleeping nodes are lost. We present new deterministic consensus algorithms that tolerate up to f < n crash failures, where n is the number of nodes. Our algorithms match the optimal time complexity lower bound of f + 1 rounds. For multi-value consensus, where the input values are chosen from some possibly large set, we achieve an energy complexity of [EQUATION] rounds, whereas for binary consensus, we show that [EQUATION] rounds are possible.

Augusta University (US)
National Science Foundation
Affordable and clean energy
Openalex Percentile: Top 86%
Distributed systems and fault tolerance
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