NDLI: On estimation problems for the G/G/∞ Queue

Content Provider	ACM Digital Library
Author	Zhang, Li Dube, Parijat Feng, Hanhua
Abstract	We consider estimation problems in G/G/∞ queue under incomplete information. Specifically, we are interested in scenarios where it is infeasible to track each individual job in the system and only aggregate statistics are known or observable. We first show that the minimum expected square estimator for the queue length process can be written as the sum of the minimum square estimators for an indicator function associated with each job, which is simply the survival function of the service time variable for each job. We also obtain tight lower and upper bounds on the time average of the square estimation error. Next we look at the inverse problem of estimating the service time distribution when the observed process is only the queue length process. We develop an on-line stochastic-optimization based estimation algorithm for the service time distribution and study its convergence under different parameter settings.
Starting Page	40
Ending Page	42
Page Count	3
File Format	PDF
ISSN	01635999
DOI	10.1145/2160803.2160854
Journal	ACM SIGMETRICS Performance Evaluation Review (PERV)
Volume Number	39
Issue Number	3
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-01-10
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	G/g/∞ queue Estimation Mean square estimation error Stochastic optimization
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Hardware and Architecture Software

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