Online matching for the multiclass stochastic block model

Abstract We consider the problem of sequential matching in a stochastic block model with several classes of nodes and generic compatibility constraints. When the probabilities of connections do not scale with the size of the graph, we show that under the Ncond condition, a simple max-weight type policy allows us to attain an asymptotically perfect matching while no sequential algorithm attains perfect matching otherwise. The proof relies on a specific Markovian representation of the dynamics associated with Lyapunov techniques.

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Publication Details

Journal
Journal of Applied Probability
Published
2025-07-21
DOI
https://doi.org/10.1017/jpr.2025.22
Primary Topic
Advanced Queuing Theory Analysis
Type
article
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article

Online matching for the multiclass stochastic block model

Nahuel Soprano-Loto, Pascal Moyal, Matthieu Jonckheere
1 links
Journal of Applied Probability
Advanced Queuing Theory Analysis
article

Online matching for the multiclass stochastic block model

Nahuel Soprano-Loto, Pascal Moyal, Matthieu Jonckheere
article en

Abstract

Abstract We consider the problem of sequential matching in a stochastic block model with several classes of nodes and generic compatibility constraints. When the probabilities of connections do not scale with the size of the graph, we show that under the Ncond condition, a simple max-weight type policy allows us to attain an asymptotically perfect matching while no sequential algorithm attains perfect matching otherwise. The proof relies on a specific Markovian representation of the dynamics associated with Lyapunov techniques.

Journal of Applied ProbabilityVol. 62(4)
Centre National de la Recherche Scientifique (FR), Université de Lorraine (FR)
Openalex Percentile: Top 70%
Advanced Queuing Theory Analysis
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