Plurality Consensus in Arbitrary Graphs: Lessons Learned from Load Balancing
- Submitting institution
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University of Durham
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 105825
- Type
- E - Conference contribution
- DOI
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10.4230/LIPIcs.ESA.2016.10
- Title of conference / published proceedings
- 24th Annual European Symposium on Algorithms (ESA 2016)
- First page
- 10:1
- Volume
- -
- Issue
- -
- ISSN
- 18688969
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2016
- URL
-
https://doi.org/10.4230/LIPIcs.ESA.2016.10
- Supplementary information
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-
- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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4
- Research group(s)
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B - Algorithms and Complexity
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- A preliminary version of this paper was mentioned in the Bulletin of the EATCS #126 in a survey on "Recent Results in Population Protocols for Exact Majority and Leader Election” as extending the previous results on majority protocols to k≥2 opinions (plurality voting) and arbitrary graphs.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -