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Large-scale join-idle-queue system with general service times. / Foss, S.; Stolyar, A. L.

In: Journal of Applied Probability, Vol. 54, No. 4, 01.12.2017, p. 995-1007.

Research output: Contribution to journalArticlepeer-review

Harvard

Foss, S & Stolyar, AL 2017, 'Large-scale join-idle-queue system with general service times', Journal of Applied Probability, vol. 54, no. 4, pp. 995-1007. https://doi.org/10.1017/jpr.2017.49

APA

Foss, S., & Stolyar, A. L. (2017). Large-scale join-idle-queue system with general service times. Journal of Applied Probability, 54(4), 995-1007. https://doi.org/10.1017/jpr.2017.49

Vancouver

Foss S, Stolyar AL. Large-scale join-idle-queue system with general service times. Journal of Applied Probability. 2017 Dec 1;54(4):995-1007. doi: 10.1017/jpr.2017.49

Author

Foss, S. ; Stolyar, A. L. / Large-scale join-idle-queue system with general service times. In: Journal of Applied Probability. 2017 ; Vol. 54, No. 4. pp. 995-1007.

BibTeX

@article{e1809524973847618dbc068bb03cb323,
title = "Large-scale join-idle-queue system with general service times",
abstract = "A parallel server system with n identical servers is considered. The service time distribution has a finite mean 1 / μ, but otherwise is arbitrary. Arriving customers are routed to one of the servers immediately upon arrival. The join-idle-queue routeing algorithm is studied, under which an arriving customer is sent to an idle server, if such is available, and to a randomly uniformly chosen server, otherwise. We consider the asymptotic regime where n → and the customer input flow rate is λn. Under the condition λ / μ < 1/2, we prove that, as n → the sequence of (appropriately scaled) stationary distributions concentrates at the natural equilibrium point, with the fraction of occupied servers being constant at λ / μ. In particular, this implies that the steady-state probability of an arriving customer waiting for service vanishes.",
keywords = "asymptotic optimality, fluid limit, join-idle-queue, Large-scale service system, load balancing, pull-based load distribution, stationary distribution, LOAD DISTRIBUTION, SERVERS",
author = "S. Foss and Stolyar, {A. L.}",
year = "2017",
month = dec,
day = "1",
doi = "10.1017/jpr.2017.49",
language = "English",
volume = "54",
pages = "995--1007",
journal = "Journal of Applied Probability",
issn = "0021-9002",
publisher = "Cambridge University Press",
number = "4",

}

RIS

TY - JOUR

T1 - Large-scale join-idle-queue system with general service times

AU - Foss, S.

AU - Stolyar, A. L.

PY - 2017/12/1

Y1 - 2017/12/1

N2 - A parallel server system with n identical servers is considered. The service time distribution has a finite mean 1 / μ, but otherwise is arbitrary. Arriving customers are routed to one of the servers immediately upon arrival. The join-idle-queue routeing algorithm is studied, under which an arriving customer is sent to an idle server, if such is available, and to a randomly uniformly chosen server, otherwise. We consider the asymptotic regime where n → and the customer input flow rate is λn. Under the condition λ / μ < 1/2, we prove that, as n → the sequence of (appropriately scaled) stationary distributions concentrates at the natural equilibrium point, with the fraction of occupied servers being constant at λ / μ. In particular, this implies that the steady-state probability of an arriving customer waiting for service vanishes.

AB - A parallel server system with n identical servers is considered. The service time distribution has a finite mean 1 / μ, but otherwise is arbitrary. Arriving customers are routed to one of the servers immediately upon arrival. The join-idle-queue routeing algorithm is studied, under which an arriving customer is sent to an idle server, if such is available, and to a randomly uniformly chosen server, otherwise. We consider the asymptotic regime where n → and the customer input flow rate is λn. Under the condition λ / μ < 1/2, we prove that, as n → the sequence of (appropriately scaled) stationary distributions concentrates at the natural equilibrium point, with the fraction of occupied servers being constant at λ / μ. In particular, this implies that the steady-state probability of an arriving customer waiting for service vanishes.

KW - asymptotic optimality

KW - fluid limit

KW - join-idle-queue

KW - Large-scale service system

KW - load balancing

KW - pull-based load distribution

KW - stationary distribution

KW - LOAD DISTRIBUTION

KW - SERVERS

UR - http://www.scopus.com/inward/record.url?scp=85041353326&partnerID=8YFLogxK

U2 - 10.1017/jpr.2017.49

DO - 10.1017/jpr.2017.49

M3 - Article

AN - SCOPUS:85041353326

VL - 54

SP - 995

EP - 1007

JO - Journal of Applied Probability

JF - Journal of Applied Probability

SN - 0021-9002

IS - 4

ER -

ID: 9445322