scholarly journals Bounds for the variance of the busy period of the M/G/∞ queue

1984 ◽  
Vol 16 (4) ◽  
pp. 929-932 ◽  
Author(s):  
M. F. Ramalhoto
Keyword(s):  
Distribution Function ◽  
Lower Bounds ◽  
Service Time ◽  
Time Distribution ◽  
Busy Period ◽  
Random Variable ◽  
Upper Bounds ◽  
Upper And Lower Bounds ◽  
Service Time Distribution ◽  
Lower And Upper Bounds

Some bounds for the variance of the busy period of an M/G/∞ queue are calculated as functions of parameters of the service-time distribution function. For any type of service-time distribution function, upper and lower bounds are evaluated in terms of the intensity of traffic and the coefficient of variation of the service time. Other lower and upper bounds are derived when the service time is a NBUE, DFR or IMRL random variable. The variance of the busy period is also related to the variance of the number of busy periods that are initiated in (0, t] by renewal arguments.

scholarly journals Bounds for the variance of the busy period of the M/G/∞ queue

1984 ◽  
Vol 16 (04) ◽  
pp. 929-932
Author(s):  
M. F. Ramalhoto
Keyword(s):  
Distribution Function ◽  
Lower Bounds ◽  
Service Time ◽  
Time Distribution ◽  
Busy Period ◽  
Random Variable ◽  
Upper Bounds ◽  
Upper And Lower Bounds ◽  
Service Time Distribution ◽  
Lower And Upper Bounds

Some bounds for the variance of the busy period of an M/G/∞ queue are calculated as functions of parameters of the service-time distribution function. For any type of service-time distribution function, upper and lower bounds are evaluated in terms of the intensity of traffic and the coefficient of variation of the service time. Other lower and upper bounds are derived when the service time is a NBUE, DFR or IMRL random variable. The variance of the busy period is also related to the variance of the number of busy periods that are initiated in (0, t] by renewal arguments.

On the integral of the workload process of the single server queue

2003 ◽  
Vol 40 (01) ◽  
pp. 200-225 ◽  
Author(s):  
A. A. Borovkov ◽  
O. J. Boxma ◽  
Z. Palmowski
Keyword(s):  
Service Time ◽  
Time Distribution ◽  
Busy Period ◽  
Single Server ◽  
Service Time Distribution ◽  
Whittaker Functions ◽  
Single Server Queue ◽  
Stieltjes Transform ◽  
Server Queue ◽  
Sequential Approximation

This paper is devoted to a study of the integral of the workload process of the single server queue, in particular during one busy period. Firstly, we find asymptotics of the area 𝒜 swept under the workload process W(t) during the busy period when the service time distribution has a regularly varying tail. We also investigate the case of a light-tailed service time distribution. Secondly, we consider the problem of obtaining an explicit expression for the distribution of 𝒜. In the general GI/G/1 case, we use a sequential approximation to find the Laplace—Stieltjes transform of 𝒜. In the M/M/1 case, this transform is obtained explicitly in terms of Whittaker functions. Thirdly, we consider moments of 𝒜 in the GI/G/1 queue. Finally, we show asymptotic normality of .

On the busy period of the modified GI/G/1 queue

1973 ◽  
Vol 10 (01) ◽  
pp. 192-197 ◽  
Author(s):  
A. G. Pakes
Keyword(s):  
Laplace Transform ◽  
Service Time ◽  
Time Distribution ◽  
Busy Period ◽  
Service Time Distribution ◽  
Duality Results ◽  
The Laplace Transform ◽  
Period Duration

Proceeding from duality results for the GI/G/1 queue, this paper obtains the probability of the number served in a busy period of aGI/G/1 system where customers initiating a busy period have a different service time distribution from other customers. Using duality arguments for processes with interchangeable increments, the Laplace transform of the busy period duration is found for a modified GI/M/1 queue.

M/Ck/1 Queue with Impatient Customers

2016 ◽  
pp. 22-37
Author(s):  
Umay Uzunoglu Kocer
Keyword(s):  
Service Time ◽  
Time Distribution ◽  
Random Variable ◽  
Death Process ◽  
Single Server ◽  
Service Time Distribution ◽  
Birth And Death Process ◽  
Impatient Customers ◽  
Constant Rate ◽  
Long Time

A single-server queuing system with impatient customers and Coxian service is examined. It is assumed that arrivals are Poisson with a constant rate. When the server is busy upon an arrival, customer joins the queue and there is an infinite capacity of the queue. Since the variance of the service time is relatively high, the service time distribution is characterized by k-phase Cox distribution. Due to the high variability of service times and since some of the services take extremely long time, customers not only in the queue, but also in the service may become impatient. Each customer, upon arrival, activates an individual timer and starts his patience time. The patience time for each customer is a random variable which has exponential distribution. If the service does not completed before the customer's time expires, the customer abandons the queue never to return. The model is expressed as birth-and-death process and the balance equations are provided.

Computational analysis of single-server bulk-service queues, M/GY/ 1

1989 ◽  
Vol 21 (1) ◽  
pp. 207-225 ◽  
Author(s):  
G. Brière ◽  
M. L. Chaudhry
Keyword(s):  
Service Time ◽  
Flexible Manufacturing ◽  
Time Distribution ◽  
Random Variable ◽  
Single Server ◽  
Service Time Distribution ◽  
Computationally Efficient ◽  
Uniform Distributions ◽  
Bulk Service ◽  
Number Of Customers

Algorithms are proposed for the numerical inversion of the analytical solutions obtained through classical transform methods. We compute steady-state probabilities and moments of the number of customers in the system (or in the queue) at three different epochs—postdeparture, random, and prearrival—for models of the type M/GY/1, where the capacity of the single server is a random variable. This implies first finding roots of the characteristic equation, which is detailed in an appendix for a general service time distribution. Numerical results, given a service time distribution, are illustrated through graphs and tables for cases covered in this study: deterministic, Erlang, hyperexponential, and uniform distributions. In all cases, the proposed method is computationally efficient and accurate, even for high values of the queueing parameters. The procedure is adaptable to other models in queueing theory (especially bulk queues), to problems in inventory control, transportation, flexible manufacturing process, etc. Exact results that can be obtained from the algorithms presented here will be found useful to test inequalities, bounds, or approximations.

On the integral of the workload process of the single server queue

2003 ◽  
Vol 40 (1) ◽  
pp. 200-225 ◽  
Author(s):  
A. A. Borovkov ◽  
O. J. Boxma ◽  
Z. Palmowski
Keyword(s):  
Service Time ◽  
Time Distribution ◽  
Busy Period ◽  
Single Server ◽  
Service Time Distribution ◽  
Whittaker Functions ◽  
Single Server Queue ◽  
Stieltjes Transform ◽  
Server Queue ◽  
Sequential Approximation

This paper is devoted to a study of the integral of the workload process of the single server queue, in particular during one busy period. Firstly, we find asymptotics of the area 𝒜 swept under the workload process W(t) during the busy period when the service time distribution has a regularly varying tail. We also investigate the case of a light-tailed service time distribution. Secondly, we consider the problem of obtaining an explicit expression for the distribution of 𝒜. In the general GI/G/1 case, we use a sequential approximation to find the Laplace—Stieltjes transform of 𝒜. In the M/M/1 case, this transform is obtained explicitly in terms of Whittaker functions. Thirdly, we consider moments of 𝒜 in the GI/G/1 queue. Finally, we show asymptotic normality of .

Computational analysis of single-server bulk-service queues, M/GY / 1

1989 ◽  
Vol 21 (01) ◽  
pp. 207-225
Author(s):  
G. Brière ◽  
M. L. Chaudhry
Keyword(s):  
Service Time ◽  
Flexible Manufacturing ◽  
Time Distribution ◽  
Random Variable ◽  
Single Server ◽  
Service Time Distribution ◽  
Computationally Efficient ◽  
Uniform Distributions ◽  
Bulk Service ◽  
Number Of Customers

Algorithms are proposed for the numerical inversion of the analytical solutions obtained through classical transform methods. We compute steady-state probabilities and moments of the number of customers in the system (or in the queue) at three different epochs—postdeparture, random, and prearrival—for models of the type M/GY/1, where the capacity of the single server is a random variable. This implies first finding roots of the characteristic equation, which is detailed in an appendix for a general service time distribution. Numerical results, given a service time distribution, are illustrated through graphs and tables for cases covered in this study: deterministic, Erlang, hyperexponential, and uniform distributions. In all cases, the proposed method is computationally efficient and accurate, even for high values of the queueing parameters. The procedure is adaptable to other models in queueing theory (especially bulk queues), to problems in inventory control, transportation, flexible manufacturing process, etc. Exact results that can be obtained from the algorithms presented here will be found useful to test inequalities, bounds, or approximations.

scholarly journals Fitting Discrete Distributions on the First Two Moments

1995 ◽  
Vol 9 (4) ◽  
pp. 623-632 ◽  
Author(s):  
Ivo Adan ◽  
Michel van Eenige ◽  
Jacques Resing
Keyword(s):  
Service Time ◽  
Iteration Method ◽  
Time Distribution ◽  
Discrete Distribution ◽  
Random Variable ◽  
Numerical Results ◽  
Discrete Distributions ◽  
Service Time Distribution ◽  
Excellent Performance ◽  
Simple Method

In this paper we present a simple method to fit a discrete distribution on the first two moments of a given random variable. With the Fitted distribution we solve approximately Lindley's equation for the D/G/1 queue with discrete service-time distribution using a moment-iteration method. Numerical results show excellent performance of the method.

scholarly journals Spaces with high topological complexity

2014 ◽  
Vol 144 (4) ◽  
pp. 761-773
Author(s):  
Aleksandra Franc ◽  
Petar Pavešić
Keyword(s):  
Lower Bounds ◽  
Upper Bounds ◽  
Upper And Lower Bounds ◽  
Topological Complexity ◽  
Lower And Upper Bounds ◽  
Cw Complex ◽  
The Difference

By a formula of Farber, the topological complexity TC(X) of a (p − 1)-connected m-dimensional CW-complex X is bounded above by (2m + 1)/p + 1. We show that the same result holds for the monoidal topological complexity TCM(X). In a previous paper we introduced various lower bounds for TCM(X), such as the nilpotency of the ring H*(X × X, Δ(X)), and the weak and stable (monoidal) topological complexity wTCM(X) and σTCM(X). In general, the difference between these upper and lower bounds can be arbitrarily large. In this paper we investigate spaces with topological complexity close to the maximal value given by Farber's formula. We show that in these cases the gap between the lower and upper bounds is narrow and TC(X) often coincides with the lower bounds.

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