Tightness of stationary distributions of a flexible-server system in the Halfin-Whitt asymptotic regime

A large-scale flexible service system with two large server pools and two types of customers is considered. Servers in pool 1 can only serve type 1 customers, while server in pool 2 are flexible – they can serve both types 1 and 2. (This is a so-called “N-system.”) The customer arrival processes are...

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Bibliographic Details
Main Author: Alexander L. Stolyar
Format: Article
Language:English
Published: Institute for Operations Research and the Management Sciences (INFORMS) 2015-12-01
Series:Stochastic Systems
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Online Access:http://www.i-journals.org/ssy/viewarticle.php?id=139&layout=abstract
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Summary:A large-scale flexible service system with two large server pools and two types of customers is considered. Servers in pool 1 can only serve type 1 customers, while server in pool 2 are flexible – they can serve both types 1 and 2. (This is a so-called “N-system.”) The customer arrival processes are Poisson and customer service requirements are independent exponentially distributed. The service rate of a customer depends both on its type and the pool where it is served. A priority service discipline, where type 2 has priority in pool 2, and type 1 prefers pool 1, is considered. We consider the Halfin-Whitt asymptotic regime, where the arrival rate of customers and the number of servers in each pool increase to infinity in proportion to a scaling parameter n, while the overall system capacity exceeds its load by O(√n). <br/> For this system we prove tightness of diffusion-scaled stationary distributions. Our approach relies on a single common Lyapunov function <i>G</i><sup>(<i>n</i>)</sup>(<i>x</i>), depending on parameter <i>n</i> and defined on the entire state space as a functional of the drift-based fluid limits (DFL). Specifically, <i>G</i><sup>(<i>n</i>)</sup>(<i>x</i>)=∫<sup>∞</sup><sub>0</sub><i>g</i>(<i>y</i><sup>(<i>n</i>)</sup>(<i>t</i>))<i>dt</i>, where <i>y</i><sup>(<i>n</i>)</sup>(⋅) is the DFL starting at <i>x</i>, and <i>g</i>(⋅) is a “distance” to the origin. (<i>g</i>(⋅) is same for all <i>n</i>). The key part of the analysis is the study of the (first and second) derivatives of the DFLs and function <i>G</i><sup>(<i>n</i>)</sup>(<i>x</i>). The approach, as well as many parts of the analysis, are quite generic and may be of independent interest.
ISSN:1946-5238
1946-5238