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Determining Majority in Networks with Local Interactions and very Small Local Memory

Distributed, Parallel, and Cluster Computing · Submitted 30 Apr 2014

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim As we prove, this protocol is optimal, in the sense that there is no population protocol that always computes majority with fewer than 4 states per vertex.

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arXiv ID1404.7671 (version 1)
Pith IDLN54JMLA, Pith's permanent record of this paper and its review
CitationChristoforos L. Raptopoulos, George B. Mertzios, Paul G. Spirakis, Sotiris E. Nikoletseas. "Determining Majority in Networks with Local Interactions and very Small Local Memory." arXiv:1404.7671 (2014). https://pith.science/paper/LN54JMLA
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What the abstract itself states, as probabilities: claims first 0.08 · states limitation 0.83 · human participants 0.02 · controlled comparison 0.09 · randomized assignment 0.75 · states quantitative result 0.95 · compares with prior results 0.94 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

We study here the problem of determining the majority type in an arbitrary connected network, each vertex of which has initially two possible types. The vertices may have a few additional possible states and can interact in pairs only if they share an edge. Any (population) protocol is required to stabilize in the initial majority. We first present and analyze a protocol with 4 states per vertex that always computes the initial majority value, under any fair scheduler. As we prove, this protocol is optimal, in the sense that there is no population protocol that always computes majority with fewer than 4 states per vertex. However this does not rule out the existence of a protocol with 3 states per vertex that is correct with high probability. To this end, we examine a very natural majority protocol with 3 states per vertex, introduced in [Angluin et al. 2008] where its performance has been analyzed for the clique graph. We study the performance of this protocol in arbitrary networks. We prove that, when the two initial states are put uniformly at random on the vertices, this protocol converges to the initial majority with probability higher than the probability of converging to the initial minority. In contrast, we present an infinite family of graphs, on which the protocol can fail whp, even when the difference between the initial majority and the initial minority is $n - \Theta(\ln{n})$. We also present another infinite family of graphs in which the protocol of Angluin et al. takes an expected exponential time to converge. These two negative results build upon a very positive result concerning the robustness of the protocol on the clique. Surprisingly, the resistance of the clique to failure causes the failure in general graphs. Our techniques use new domination and coupling arguments for suitably defined processes whose dynamics capture the antagonism between the states involved.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 We study here the problem of determining the majority type in an arbitrary connected network, each vertex of which has initially two possible types. background 0.87 0.30 0.03 asserted 0.78
s1 The vertices may have a few additional possible states and can interact in pairs only if they share an edge. background 0.94 0.13 0.02 hedged possibility 0.92
s2 Any (population) protocol is required to stabilize in the initial majority. background 0.97 0.08 0.06 asserted 0.98
s3 We first present and analyze a protocol with 4 states per vertex that always computes the initial majority value, under any fair scheduler. contribution 0.91 0.95 0.28 asserted 1.00
s4 As we prove, this protocol is optimal, in the sense that there is no population protocol that always computes majority with fewer than 4 states per vertex. result 0.91 0.86 0.35 asserted 1.00
s5 However this does not rule out the existence of a protocol with 3 states per vertex that is correct with high probability. gap 0.85 0.26 0.07 hedged possibility 0.90
s6 To this end, we examine a very natural majority protocol with 3 states per vertex, introduced in [Angluin et al. 2008] where its performance has been analyzed for the clique graph. background 0.48 0.11 0.04 asserted 0.94
s7 We study the performance of this protocol in arbitrary networks. contribution 0.98 0.81 0.03 asserted 0.57
s8 We prove that, when the two initial states are put uniformly at random on the vertices, this protocol converges to the initial majority with probability higher than the probability of converging to the initial minority. result 1.00 0.90 0.13 asserted 1.00
s9 In contrast, we present an infinite family of graphs, on which the protocol can fail whp, even when the difference between the initial majority and the initial minority is $n - \Theta(\ln{n})$. result 0.97 0.94 0.18 asserted 0.99
s10 We also present another infinite family of graphs in which the protocol of Angluin et al. takes an expected exponential time to converge. result 0.97 0.93 0.07 asserted 1.00
s11 These two negative results build upon a very positive result concerning the robustness of the protocol on the clique. interpretation 0.79 0.64 0.08 asserted 0.99
s12 Surprisingly, the resistance of the clique to failure causes the failure in general graphs. interpretation 0.93 0.78 0.15 asserted 1.00
s13 Our techniques use new domination and coupling arguments for suitably defined processes whose dynamics capture the antagonism between the states involved. method 0.99 0.87 0.04 asserted 1.00

What kind of paper the classifier reports this is: theoretical result 1.00 · evidence from proof or derivation 1.00.

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Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

We study here the problem of determining the majority type in an arbitrary connected network, each vertex of which has initially two possible types. The vertices may have a few additional possible states and can interact in pairs only if they share an edge. Any (population) protocol is required to stabilize in the initial majority. We first present and analyze a protocol with 4 states per vertex that always computes the initial majority value, under any fair scheduler. As we prove, this protocol is optimal, in the sense that there is no population protocol that always computes majority with fewer than 4 states per vertex. However this does not rule out the existence of a protocol with 3 states per vertex that is correct with high probability. To this end, we examine a very natural majority protocol with 3 states per vertex, introduced in [Angluin et al. 2008] where its performance has been analyzed for the clique graph. We study the performance of this protocol in arbitrary networks. We prove that, when the two initial states are put uniformly at random on the vertices, this protocol converges to the initial majority with probability higher than the probability of converging to the initial minority. In contrast, we present an infinite family of graphs, on which the protocol can fail whp, even when the difference between the initial majority and the initial minority is $n - \Theta(\ln{n})$. We also present another infinite family of graphs in which the protocol of Angluin et al. takes an expected exponential time to converge. These two negative results build upon a very positive result concerning the robustness of the protocol on the clique. Surprisingly, the resistance of the clique to failure causes the failure in general graphs. Our techniques use new domination and coupling arguments for suitably defined processes whose dynamics capture the antagonism between the states involved.

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