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Bibliographic Details
Main Authors: Hurtado-Lange, Daniela, Grosof, Izzy
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2603.00387
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author Hurtado-Lange, Daniela
Grosof, Izzy
author_facet Hurtado-Lange, Daniela
Grosof, Izzy
contents In parallel-server systems with a single stream of arrivals (a.k.a. load balancing), Join-the-Shortest-Queue (JSQ) is a popular routing algorithm. There is extensive literature studying this system in various asymptotic regimes, but all assume constant parameters (arrival and service rates). We study the JSQ system with Markov-modulated parameters and heterogeneous servers. Our main contributions are: (i) We compute the heavy-traffic distribution of the scaled vector of queue lengths; (ii) We utilize a novel hybrid methodology that combines the Transform Method for queue-lengths analysis and the Poisson equation; (iii) We provide sufficient conditions to ensure state space collapse, showing provable balancing power of JSQ for heterogeneous servers. Unlike other studies involving Markov-modulated queues, these conditions don't depend on the mixing time of the modulating chain and are valid for a countably infinite state space. We numerically demonstrate the strength of our results under moderate traffic intensities and showcase their independence from the corresponding mixing times.
format Preprint
id arxiv_https___arxiv_org_abs_2603_00387
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Markov Modulated JSQ in Heavy Traffic Via the Poisson Equation
Hurtado-Lange, Daniela
Grosof, Izzy
Probability
In parallel-server systems with a single stream of arrivals (a.k.a. load balancing), Join-the-Shortest-Queue (JSQ) is a popular routing algorithm. There is extensive literature studying this system in various asymptotic regimes, but all assume constant parameters (arrival and service rates). We study the JSQ system with Markov-modulated parameters and heterogeneous servers. Our main contributions are: (i) We compute the heavy-traffic distribution of the scaled vector of queue lengths; (ii) We utilize a novel hybrid methodology that combines the Transform Method for queue-lengths analysis and the Poisson equation; (iii) We provide sufficient conditions to ensure state space collapse, showing provable balancing power of JSQ for heterogeneous servers. Unlike other studies involving Markov-modulated queues, these conditions don't depend on the mixing time of the modulating chain and are valid for a countably infinite state space. We numerically demonstrate the strength of our results under moderate traffic intensities and showcase their independence from the corresponding mixing times.
title Markov Modulated JSQ in Heavy Traffic Via the Poisson Equation
topic Probability
url https://arxiv.org/abs/2603.00387