Note on the output of a queuing system

1969 ◽  
Vol 6 (02) ◽  
pp. 459-461 ◽  
Author(s):  
Duane C. Boes

Consider a queuing system that has c servers and d waiting positions. Assume that the input is Poisson with rate α and the service times are exponential with mean β –1. Further assume the following: (i) a customer arriving when all servers are busy and all waiting positions are occupied is “cleared” from the system; (ii) a customer arriving when all servers are busy and not all waiting positions are occupied waits with probability 1 – ζ and “balks” or “clears” with probability ζ; (iii) a customer arriving when not all servers are busy commences service immediately (never balks); and, (iv) a customer who is waiting for service may “defect”, the distribution of time until a waiting customer defects being given by an exponential distribution with mean γ–1. Also, the usual independence assumptions, which make the process that is described by the number in the system at time t Markov, are assumed. An “output” of this queuing system is defined to occur whenever a service completion occurs, or whenever an arrival “clears” or “balks”, or whenever a waiting customer “defects”. Thus the output is a pooling of service completion epochs, the epochs when arrivals are cleared, the epochs when arrivals balk, and the defection epochs.

1969 ◽  
Vol 6 (2) ◽  
pp. 459-461 ◽  
Author(s):  
Duane C. Boes

Consider a queuing system that has c servers and d waiting positions. Assume that the input is Poisson with rate α and the service times are exponential with mean β–1. Further assume the following: (i) a customer arriving when all servers are busy and all waiting positions are occupied is “cleared” from the system; (ii) a customer arriving when all servers are busy and not all waiting positions are occupied waits with probability 1 – ζ and “balks” or “clears” with probability ζ; (iii) a customer arriving when not all servers are busy commences service immediately (never balks); and, (iv) a customer who is waiting for service may “defect”, the distribution of time until a waiting customer defects being given by an exponential distribution with mean γ–1. Also, the usual independence assumptions, which make the process that is described by the number in the system at time t Markov, are assumed. An “output” of this queuing system is defined to occur whenever a service completion occurs, or whenever an arrival “clears” or “balks”, or whenever a waiting customer “defects”. Thus the output is a pooling of service completion epochs, the epochs when arrivals are cleared, the epochs when arrivals balk, and the defection epochs.


1970 ◽  
Vol 7 (2) ◽  
pp. 457-464 ◽  
Author(s):  
D. G. Tambouratzis

SummaryThe aim of the present note is to give an alternative simpler proof to a result of Belyaev [1], namely that in a loss system of n servers with recurrent input and negative exponential service times the intervals between losses, suitably scaled to have constant mean, tend to a negative exponential distribution as n tends to infinity.


2013 ◽  
Vol 756-759 ◽  
pp. 2470-2474
Author(s):  
Mian Zhang

We consider a finite butter single server queue with batch arrival, where server serves a limited number of customer before going for vacation (s).The inter arrival times of batches are assumed to be independent and geometrically distribute. The service times and the vacation times of the server are generally distributed and their durations are integral multiples of slots duration. We obtain queue length distributions at service completion, vacation termination and arbitrary epochs.


Author(s):  
P. Vijaya Laxmi ◽  
Veena Goswami ◽  
K. Jyothsna

This chapter analyzes a steady-state finite buffer M/M/1 working vacation queue wherein the customers can balk or renege. Unlike the classical vacation queues, the server can still render service to customers during the working vacations, at a different rate rather than completely terminating the service. The inter-arrival times of customers follow exponential distribution. The arriving customers either decide not to join the queue (that is, balk) with a probability or leave the queue after joining without getting served due to impatience (that is, renege) according to negative exponential distribution. The service times during a regular busy period, service times during a working vacation period, and vacation times are all independent and exponentially distributed random variables. Using Markov process, the steady-state equations are set and the steady-state system length distributions at arbitrary epoch are derived using blocked matrix method. A cost model is formulated to determine the optimum service rate. Sensitivity analysis is carried out to investigate the impact of the system parameters on various performance indices.


1970 ◽  
Vol 7 (02) ◽  
pp. 457-464
Author(s):  
D. G. Tambouratzis

Summary The aim of the present note is to give an alternative simpler proof to a result of Belyaev [1], namely that in a loss system of n servers with recurrent input and negative exponential service times the intervals between losses, suitably scaled to have constant mean, tend to a negative exponential distribution as n tends to infinity.


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