TY - JOUR
T1 - Optimal Scheduling of Critically Loaded Multiclass GI/M/n+M Queues in an Alternating Renewal Environment
AU - Arapostathis, Ari
AU - Pang, Guodong
AU - Zheng, Yi
N1 - Funding Information:
This research was supported in part by the Army Research Office through Grant W911NF-17-1-001, in part by the National Science Foundation through Grants DMS-1715210, CMMI-1635410 and DMS-1715875, and in part by the Office of Naval Research through Grant N00014-16-1-2956 and was approved for public release under DCN #43-5442-19.
Publisher Copyright:
© 2020, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2021/10
Y1 - 2021/10
N2 - In this paper, we study optimal control problems for multiclass GI/ M/ n+ M queues in an alternating renewal (up–down) random environment in the Halfin–Whitt regime. Assuming that the downtimes are asymptotically negligible and only the service processes are affected, we show that the limits of the diffusion-scaled state processes under non-anticipative, preemptive, work-conserving scheduling policies, are controlled jump diffusions driven by a compound Poisson jump process. We establish the asymptotic optimality of the infinite-horizon discounted and long-run average (ergodic) problems for the queueing dynamics. Since the process counting the number of customers in each class is not Markov, the usual martingale arguments for convergence of mean empirical measures cannot be applied. We surmount this obstacle by demonstrating the convergence of the generators of an augmented Markovian model which incorporates the age processes of the renewal interarrival times and downtimes. We also establish long-run average moment bounds of the diffusion-scaled queueing processes under some (modified) priority scheduling policies. This is accomplished via Foster–Lyapunov equations for the augmented Markovian model.
AB - In this paper, we study optimal control problems for multiclass GI/ M/ n+ M queues in an alternating renewal (up–down) random environment in the Halfin–Whitt regime. Assuming that the downtimes are asymptotically negligible and only the service processes are affected, we show that the limits of the diffusion-scaled state processes under non-anticipative, preemptive, work-conserving scheduling policies, are controlled jump diffusions driven by a compound Poisson jump process. We establish the asymptotic optimality of the infinite-horizon discounted and long-run average (ergodic) problems for the queueing dynamics. Since the process counting the number of customers in each class is not Markov, the usual martingale arguments for convergence of mean empirical measures cannot be applied. We surmount this obstacle by demonstrating the convergence of the generators of an augmented Markovian model which incorporates the age processes of the renewal interarrival times and downtimes. We also establish long-run average moment bounds of the diffusion-scaled queueing processes under some (modified) priority scheduling policies. This is accomplished via Foster–Lyapunov equations for the augmented Markovian model.
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U2 - 10.1007/s00245-020-09698-9
DO - 10.1007/s00245-020-09698-9
M3 - Article
AN - SCOPUS:85087622090
SN - 0095-4616
VL - 84
SP - 1857
EP - 1901
JO - Applied Mathematics and Optimization
JF - Applied Mathematics and Optimization
IS - 2
ER -