ON MARKOVIAN QUEUES WITH SINGLE WORKING VACATION AND BERNOULLI INTERRUPTIONS. Issue 3 (July 2022)

• Record Type: Journal Article
• Authors: Tian, Ruiling; Zhang, Zhe George; Su, Siping
• Is Part Of: Probability in the engineering and informational sciences. Volume 36:Issue 3(2022)
• Page Start: 616
• Page End: 643
• Publication Date: 2022-07
• Subjects: Bernoulli vacation interruptions -- equilibrium balking strategy -- queuing system -- social welfare -- working vacation; Probabilities -- Periodicals; Engineering -- Statistical methods -- Periodicals; Information science -- Statistical methods -- Periodicals; 519.202462
• DOI: 10.1017/S0269964820000704
• Languages: English
• ISSNs: 0269-9648

Abstract

Abstract : This paper considers the customers' equilibrium and socially optimal joining–balking behavior in a single-server Markovian queue with a single working vacation and Bernoulli interruptions. The model is motivated by practical service systems where the service rate can be adjusted according to whether or not the system is empty. Specifically, we focus on a single-server queue in which the server's service rate is reduced from a regular to a lower one when the system becomes empty. This lower rate period is called a working vacation for the server which may represent that part of the service facility is under a maintenance process or works on other non-queueing job, or simply for saving the energy (for a machine server case). In this paper, we assume that the working vacation period is terminated after a random period or with probability p after serving a customer in a non-empty system. Such a system is called a queue with single working vacation and Bernoulli interruptions. Customers are strategic and can make choice of joining or balking based on different levels of system information. We consider four scenarios: fully observable, almost observable, almost unobservable, and fully unobservable queue cases. Under a reward-cost structure, we analyze the customer's equilibrium and social-optimal strategies. In addition, the effects of system parameters on optimal strategies are illustrated by numerical examples.