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A Tight Analysis of the Parallel Undecided-State Dynamics with Two Colors
- Source :
- 43rd International Symposium on Mathematical Foundations of Computer Science, Leibniz International Proceedings in Informatics, Leibniz International Proceedings in Informatics (LIPIcs), 117, 43rd International Symposium on Mathematical Foundations of Computer Science (MFCS 2018), 43rd International Symposium on Mathematical Foundations of Computer Science (MFCS 2018), Aug 2018, Liverpool, United Kingdom. ⟨10.4230/LIPIcs.MFCS.2018.28⟩
- Publication Year :
- 2017
-
Abstract
- The Undecided-State Dynamics is a well-known protocol for distributed consensus. We analyze it in the parallel PULL communication model on the complete graph with n nodes for the binary case (every node can either support one of two possible colors, or be in the undecided state). An interesting open question is whether this dynamics is an efficient Self-Stabilizing protocol, namely, starting from an arbitrary initial configuration, it reaches consensus quickly (i.e., within a polylogarithmic number of rounds). Previous work in this setting only considers initial color configurations with no undecided nodes and a large bias (i.e., Theta(n)) towards the majority color. In this paper we present an unconditional analysis of the Undecided-State Dynamics that answers to the above question in the affirmative. We prove that, starting from any initial configuration, the process reaches a monochromatic configuration within O(log n) rounds, with high probability. This bound turns out to be tight. Our analysis also shows that, if the initial configuration has bias Omega(sqrt(n log n)), then the dynamics converges toward the initial majority color, with high probability.<br />Leibniz International Proceedings in Informatics (LIPIcs), 117<br />ISSN:1868-8969<br />43rd International Symposium on Mathematical Foundations of Computer Science (MFCS 2018)<br />ISBN:978-3-95977-086-6
- Subjects :
- 060201 languages & linguistics
FOS: Computer and information sciences
000 Computer science, knowledge, general works
Distributed Consensus
Settore INF/01 - Informatica
Distributed Consensus, Self-Stabilization, PULL Model, Markov Chains
06 humanities and the arts
02 engineering and technology
Markov Chains
Settore MAT/06 - Probabilita' e Statistica Matematica
PULL Model
Self-Stabilization
0602 languages and literature
Computer Science
Computer Science - Data Structures and Algorithms
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Data Structures and Algorithms (cs.DS)
[INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]
MathematicsofComputing_DISCRETEMATHEMATICS
Subjects
Details
- Language :
- English
- ISBN :
- 978-3-95977-086-6
- ISSN :
- 18688969
- ISBNs :
- 9783959770866
- Database :
- OpenAIRE
- Journal :
- 43rd International Symposium on Mathematical Foundations of Computer Science, Leibniz International Proceedings in Informatics, Leibniz International Proceedings in Informatics (LIPIcs), 117, 43rd International Symposium on Mathematical Foundations of Computer Science (MFCS 2018), 43rd International Symposium on Mathematical Foundations of Computer Science (MFCS 2018), Aug 2018, Liverpool, United Kingdom. ⟨10.4230/LIPIcs.MFCS.2018.28⟩
- Accession number :
- edsair.doi.dedup.....ad805ef16af5b53163fdfe4269850a0d
- Full Text :
- https://doi.org/10.4230/LIPIcs.MFCS.2018.28⟩