Evidence map›Paper›PMID 32132209›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2020

Communication cost of consensus for nodes with limited memory.

Giulia Fanti, Nina Holden, Yuval Peres, Gireeja Ranade

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Communication cost of consensus for nodes with limited memory.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Giulia FantiDepartment of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213.
Nina HoldenInstitute for Theoretical Studies, Swiss Federal Institute of Technology (ETH) Zürich, 8092 Zürich, Switzerland.
Yuval PeresMicrosoft Research, Redmond, WA 98052; yperes@gmail.com.
Gireeja RanadeDepartment of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motivated by applications in wireless networks and the Internet of Things, we consider a model of n nodes trying to reach consensus with high probability on their majority bit. Each node i is assigned a bit at time 0 and is a finite automaton with m bits of memory (i.e., [Formula: see text] states) and a Poisson clock. When the clock of i rings, i can choose to communicate and is then matched to a uniformly chosen node j. The nodes j and i may update their states based on the state of the other node. Previous work has focused on minimizing the time to consensus and the probability of error, while our goal is minimizing the number of communications. We show that, when [Formula: see text], consensus can be reached with linear communication cost, but this is impossible if [Formula: see text] A key step is to distinguish when nodes can become aware of knowing the majority bit and stop communicating. We show that this is impossible if their memory is too low.

Indexed as

ConsensusModels, TheoreticalInformation Storage and RetrievalInternet of ThingsWireless Technologycommunicationconsensusdistributed computingmemory

Identifiers

PMID32132209
PMCPMC7084082

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.