ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1209.5025
167
5
v1v2v3 (latest)

Global Majority Consensus by Local Majority Polling on Graphs of a Given Degree Sequence

22 September 2012
Mohammed Abdullah
M. Draief
ArXiv (abs)PDFHTML
Abstract

Suppose in a graph GGG vertices can be either red or blue. Let kkk be odd. At each time step, each vertex vvv in GGG polls kkk random neighbours and takes the majority colour. If it doesn't have kkk neighbours, it simply polls all of them, or all less one if the degree of vvv is even. We study this protocol on graphs of a given degree sequence, in the following setting: initially each vertex of GGG is red independently with probability α<12\alpha < \frac{1}{2}α<21​, and is otherwise blue. We show that if α\alphaα is sufficiently biased, then with high probability consensus is reached on the initial global majority within O(log⁡klog⁡kn)O(\log_k \log_k n)O(logk​logk​n) steps if 5≤k≤d5 \leq k \leq d5≤k≤d, and O(log⁡dlog⁡dn)O(\log_d \log_d n)O(logd​logd​n) steps if k>dk > dk>d. Here, d≥5d\geq 5d≥5 is the effective minimum degree, the smallest integer which occurs Θ(n)\Theta(n)Θ(n) times in the degree sequence. We further show that on such graphs, any local protocol in which a vertex does not change colour if all its neighbours have that same colour, takes time at least Ω(log⁡dlog⁡dn)\Omega(\log_d \log_d n)Ω(logd​logd​n), with high probability. Additionally, we demonstrate how the technique for the above sparse graphs can be applied in a straightforward manner to get bounds for the Erd\H{o}s-R\ényi random graphs in the connected regime.

View on arXiv
Comments on this paper