4.4 Article

LAW OF LARGE NUMBERS LIMITS FOR MANY-SERVER QUEUES

期刊

ANNALS OF APPLIED PROBABILITY
卷 21, 期 1, 页码 33-114

出版社

INST MATHEMATICAL STATISTICS
DOI: 10.1214/09-AAP662

关键词

Multi-server queues; GI/G/N queue; fluid limits; mean-field limits; strong law of large numbers; measure-valued processes; call centers

资金

  1. US-Israel Binational Science Foundation [BSF-2006379]
  2. Technion Fund for the Promotion of Research [2003941]
  3. Milford Bohm Chair
  4. NSF [DMS-04-06191, CMMI-1059967, CMMI-0728064, CMMI-1052750, CMMI-0928154]
  5. Directorate For Engineering
  6. Div Of Civil, Mechanical, & Manufact Inn [1052750] Funding Source: National Science Foundation
  7. Directorate For Engineering
  8. Div Of Civil, Mechanical, & Manufact Inn [1059967] Funding Source: National Science Foundation

向作者/读者索取更多资源

This work considers a many-server queueing system in which customers with independent and identically distributed service times, chosen from a general distribution, enter service in the order of arrival. The dynamics of the system are represented in terms of a process that describes the total number of customers in the system, as well as a measure-valued process that keeps track of the ages of customers in service. Under mild assumptions on the service time distribution, as the number of servers goes to infinity, a law of large numbers (or fluid) limit is established for this pair of processes. The limit is characterized as the unique solution to a coupled pair of integral equations which admits a fairly explicit representation. As a corollary, the fluid limits of several other functionals of interest, such as the waiting time, are also obtained. Furthermore, when the arrival process is time-homogeneous, the measure-valued component of the fluid limit is shown to converge to its equilibrium. Along the way, some results of independent interest are obtained, including a continuous mapping result and a maximality property of the fluid limit. A motivation for studying these systems is that they arise as models of computer data systems and call centers.

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