Control of systems with flexible multi-server pools: a shadow routing approach
A general model with multiple input flows (classes) and several flexible multi-server pools is considered. We propose a robust, generic scheme for routing new arrivals, which optimally balances server pools’ loads, without the knowledge of the flow input rates and without solving any optimization pr...
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| Published in | Queueing systems Vol. 66; no. 1; pp. 1 - 51 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Boston
Springer US
01.09.2010
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0257-0130 1572-9443 |
| DOI | 10.1007/s11134-010-9183-0 |
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| Abstract | A general model with multiple input flows (classes) and several flexible multi-server pools is considered. We propose a robust, generic scheme for routing new arrivals, which optimally balances server pools’ loads, without the knowledge of the flow input rates and without solving any optimization problem. The scheme is based on
Shadow routing
in a virtual queueing system. We study the behavior of our scheme in the Halfin–Whitt (or, QED) asymptotic regime, when server pool sizes and the input rates are scaled up simultaneously by a factor
r
growing to infinity, while keeping the system load within
of its capacity.
The main results are as follows. (i) We show that, in general, a system in a stationary regime has at least
average queue lengths, even if the so called
null-controllability
(Atar et al., Ann. Appl. Probab. 16, 1764–1804,
2006
) on a finite time interval is possible; strategies achieving this
growth rate we call
order-optimal
. (ii) We show that some natural algorithms, such as
MaxWeight
, that guarantee stability, are
not
order-optimal. (iii) Under the
complete resource pooling
condition, we prove the diffusion limit of the arrival processes into server pools, under the Shadow routing. (We conjecture that result (iii) leads to order-optimality of the Shadow routing algorithm; a formal proof of this fact is an important subject of future work.) Simulation results demonstrate good performance and robustness of our scheme. |
|---|---|
| AbstractList | A general model with multiple input flows (classes) and several flexible multi-server pools is considered. We propose a robust, generic scheme for routing new arrivals, which optimally balances server pools' loads, without the knowledge of the flow input rates and without solving any optimization problem. The scheme is based on Shadow routing in a virtual queueing system. We study the behavior of our scheme in the Halfin-Whitt (or, QED) asymptotic regime, when server pool sizes and the input rates are scaled up simultaneously by a factor r growing to infinity, while keeping the system load within O([SQRT r]) of its capacity. The main results are as follows. (i) We show that, in general, a system in a stationary regime has at least O([SQRT r]) average queue lengths, even if the so called null-controllability (Atar et al., Ann. Appl. Probab. 16, 1764-1804, 2006) on a finite time interval is possible; strategies achieving this O([SQRT r]) growth rate we call order-optimal. (ii) We show that some natural algorithms, such as MaxWeight, that guarantee stability, are not order-optimal. (iii) Under the complete resource pooling condition, we prove the diffusion limit of the arrival processes into server pools, under the Shadow routing. (We conjecture that result (iii) leads to order-optimality of the Shadow routing algorithm; a formal proof of this fact is an important subject of future work.) Simulation results demonstrate good performance and robustness of our scheme.[PUBLICATION ABSTRACT] A general model with multiple input flows (classes) and several flexible multi-server pools is considered. We propose a robust, generic scheme for routing new arrivals, which optimally balances server pools’ loads, without the knowledge of the flow input rates and without solving any optimization problem. The scheme is based on Shadow routing in a virtual queueing system. We study the behavior of our scheme in the Halfin–Whitt (or, QED) asymptotic regime, when server pool sizes and the input rates are scaled up simultaneously by a factor r growing to infinity, while keeping the system load within of its capacity. The main results are as follows. (i) We show that, in general, a system in a stationary regime has at least average queue lengths, even if the so called null-controllability (Atar et al., Ann. Appl. Probab. 16, 1764–1804, 2006 ) on a finite time interval is possible; strategies achieving this growth rate we call order-optimal . (ii) We show that some natural algorithms, such as MaxWeight , that guarantee stability, are not order-optimal. (iii) Under the complete resource pooling condition, we prove the diffusion limit of the arrival processes into server pools, under the Shadow routing. (We conjecture that result (iii) leads to order-optimality of the Shadow routing algorithm; a formal proof of this fact is an important subject of future work.) Simulation results demonstrate good performance and robustness of our scheme. |
| Author | Stolyar, Alexander L. Tezcan, Tolga |
| Author_xml | – sequence: 1 givenname: Alexander L. surname: Stolyar fullname: Stolyar, Alexander L. email: stolyar@research.bell-labs.com organization: Bell Labs, Alcatel-Lucent – sequence: 2 givenname: Tolga surname: Tezcan fullname: Tezcan, Tolga organization: University of Illinois, Urbana-Champaign |
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| Keywords | Large flexible server pools Halfin–Whitt regime Many server asymptotics 90B15 Routing and scheduling 60J70 Queueing networks Shadow routing 60K25 Order-optimality Diffusion limit |
| Language | English |
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| SubjectTerms | Business and Management Call centers Computer Communication Networks Control Control algorithms Customer services Literature reviews Load Operations Research/Decision Theory Optimization Probability Theory and Stochastic Processes Scheduling Servers Supply Chain Management Systems stability Systems Theory |
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| Title | Control of systems with flexible multi-server pools: a shadow routing approach |
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