Performing Load Balancing under Constraints

Join-the-shortest queue (JSQ) and its variants have often been used in solving load balancing problems. The aim of such policies is to minimize the average system occupation, e.g., the customer's system time. In this paper, we extend the load balancing setting to include constraints that may be imposed, e.g., due to the communication network. First, we cast the problem in the framework of constrained MDPs: this permits us to address both action-dependent constraints, such as, e.g, bandwidth limitation, and state-dependent constraints, such as, e.g., minimum queue utilization. Hence, unlike the state-of-the-art approaches in load balancing, we derive new policies that satisfy the constraints while minimizing system occupancy. Extensive numerical simulations have evaluated their performance under various system settings.

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Publication Details

Published
2025-05-26
DOI
https://doi.org/10.23919/wiopt66569.2025.11123242
Citations
1
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
1.49
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Performing Load Balancing under Constraints

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article

Performing Load Balancing under Constraints

Arnob Ghosh, Ness B. Shroff, Francesco De Pellegrini, Andrea Fox, Eitan Altman
article en
1 citations

Abstract

Join-the-shortest queue (JSQ) and its variants have often been used in solving load balancing problems. The aim of such policies is to minimize the average system occupation, e.g., the customer's system time. In this paper, we extend the load balancing setting to include constraints that may be imposed, e.g., due to the communication network. First, we cast the problem in the framework of constrained MDPs: this permits us to address both action-dependent constraints, such as, e.g, bandwidth limitation, and state-dependent constraints, such as, e.g., minimum queue utilization. Hence, unlike the state-of-the-art approaches in load balancing, we derive new policies that satisfy the constraints while minimizing system occupancy. Extensive numerical simulations have evaluated their performance under various system settings.

New Jersey Institute of Technology (US), Institut national de recherche en sciences et technologies du numérique (FR), Université d'Avignon et des Pays de Vaucluse (FR), Laboratoire Informatique d'Avignon (FR), The Ohio State University (US)
Openalex Percentile: Top 14%
Distributed and Parallel Computing Systems
1.49
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Performing Load Balancing under Constraints — Arnob Ghosh, Ness B. Shroff, et al. · (2025) | TGRS Research Map | TGRS