The Annals of Applied Probability

Controlled stochastic networks in heavy traffic: Convergence of value functions

Amarjit Budhiraja and Arka P. Ghosh

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Scheduling control problems for a family of unitary networks under heavy traffic with general interarrival and service times, probabilistic routing and an infinite horizon discounted linear holding cost are studied. Diffusion control problems, that have been proposed as approximate models for the study of these critically loaded controlled stochastic networks, can be regarded as formal scaling limits of such stochastic systems. However, to date, a rigorous limit theory that justifies the use of such approximations for a general family of controlled networks has been lacking. It is shown that, under broad conditions, the value function of the suitably scaled network control problem converges to that of the associated diffusion control problem. This scaling limit result, in addition to giving a precise mathematical basis for the above approximation approach, suggests a general strategy for constructing near optimal controls for the physical stochastic networks by solving the associated diffusion control problem.

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Ann. Appl. Probab., Volume 22, Number 2 (2012), 734-791.

First available in Project Euclid: 2 April 2012

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Mathematical Reviews number (MathSciNet)

Zentralblatt MATH identifier

Primary: 60K25: Queueing theory [See also 68M20, 90B22] 68M20: Performance evaluation; queueing; scheduling [See also 60K25, 90Bxx] 90B22: Queues and service [See also 60K25, 68M20] 90B36: Scheduling theory, stochastic [See also 68M20]
Secondary: 60J70: Applications of Brownian motions and diffusion theory (population genetics, absorption problems, etc.) [See also 92Dxx]

Heavy traffic stochastic control scaling limits diffusion approximations unitary networks controlled stochastic processing networks asymptotic optimality singular control with state constraints Brownian control problem (BCP)


Budhiraja, Amarjit; Ghosh, Arka P. Controlled stochastic networks in heavy traffic: Convergence of value functions. Ann. Appl. Probab. 22 (2012), no. 2, 734--791. doi:10.1214/11-AAP784.

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