4.6 Article

An unreliable discrete-time retrial queue with probabilistic preemptive priority, balking customers and replacements of repair times

期刊

AIMS MATHEMATICS
卷 5, 期 5, 页码 4322-4344

出版社

AMER INST MATHEMATICAL SCIENCES-AIMS
DOI: 10.3934/math.2020276

关键词

discrete-time retrial queue; probabilistic preemptive priority; balking customers; starting failures; replacement

资金

  1. Scientific Research Project of Sichuan University of Science and Engineering [2017RCL56]
  2. Opening Project of Sichuan Province University Key Laboratory of Bridge Non-destruction Detecting and Engineering Computing [2019QYJ03]
  3. National Natural Science Foundation of China [71571127]

向作者/读者索取更多资源

This paper deals with a discrete-time Geo/G/1 retrial queueing system with probabilistic preemptive priority and balking customers, in which the server is subject to starting failures and replacements in the repair times may occur with some probability. If the server is found busy at an arrival epoch, the newly arriving customer either interrupts the customer in service to begin its own service with probability p or enters the orbit with probability 1-p. When an arriving customer (external or repeated) finds the server free, he must turn on the server. If the server is activated successfully, the customer receives service immediately. Otherwise, the server undergoes a repair process. If an external arrival finds that the server is under repair, he decides either to join the orbit with probability q or leaves the system completely (balking) with probability 1 - q. Applying the supplementary variable method and the generating function technique, we analyze the Markov chain underlying the considered queueing model and derive the stationary distributions under different system states, the generating functions for the number of customers in the orbit and in the system, as well as some crucial performance measures in steady state. Especially, some corresponding results under special cases are directly obtained by setting appropriate parameter values. Further, some numerical examples are provided to examine the effect of various system parameters on queueing characteristics. Finally, an operating cost function is formulated to discuss numerically a cost optimization problem.

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