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Bibliographic Details
Main Authors: Fricker, Christine, Mohamed, Hanene
Format: Preprint
Published: 2022
Subjects:
Online Access:https://arxiv.org/abs/2201.08298
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author Fricker, Christine
Mohamed, Hanene
author_facet Fricker, Christine
Mohamed, Hanene
contents The problem of reservation in a large distributed system is analyzed via a new mathematical model. A typical application is a station-based car-sharing system which can be described as a closed stochastic network where the nodes are the stations and the customers are the cars. The user can reserve the car and the parking space. In the paper, we study the evolution of the system when the reservation of parking spaces and cars is effective for all users. The asymptotic behavior of the underlying stochastic network is given when the number $N$ of stations and the fleet size increase at the same rate. The analysis involves a Markov process on a state space with dimension of order $N^2$. It is quite remarkable that the state process describing the evolution of the stations, whose dimension is of order $N$, converges in distribution, although not Markov, to an non-homogeneous Markov process. We prove this mean-field convergence. We also prove, using combinatorial arguments, that the mean-field limit has a unique equilibrium measure when the time between reserving and picking up the car is sufficiently small. This result extends the case where only the parking space can be reserved.
format Preprint
id arxiv_https___arxiv_org_abs_2201_08298
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Mean field analysis of stochastic networks with reservation
Fricker, Christine
Mohamed, Hanene
Probability
60J27, 60K25, 60K30
The problem of reservation in a large distributed system is analyzed via a new mathematical model. A typical application is a station-based car-sharing system which can be described as a closed stochastic network where the nodes are the stations and the customers are the cars. The user can reserve the car and the parking space. In the paper, we study the evolution of the system when the reservation of parking spaces and cars is effective for all users. The asymptotic behavior of the underlying stochastic network is given when the number $N$ of stations and the fleet size increase at the same rate. The analysis involves a Markov process on a state space with dimension of order $N^2$. It is quite remarkable that the state process describing the evolution of the stations, whose dimension is of order $N$, converges in distribution, although not Markov, to an non-homogeneous Markov process. We prove this mean-field convergence. We also prove, using combinatorial arguments, that the mean-field limit has a unique equilibrium measure when the time between reserving and picking up the car is sufficiently small. This result extends the case where only the parking space can be reserved.
title Mean field analysis of stochastic networks with reservation
topic Probability
60J27, 60K25, 60K30
url https://arxiv.org/abs/2201.08298