Two results in the theory of queues

1970 ◽  
Vol 7 (1) ◽  
pp. 219-226 ◽  
Author(s):  
H. Ali
Keyword(s):  
Interarrival Time ◽  
Renewal Function ◽  
Expected Number

SummaryIn this paper it is shown that the distribution of the instant of service of a customer is symmetric as between the distributions of service and interarrival time. Also U(t), the expected number of departures in (0, t), is a delayed renewal function for the GI/M/1 queue.

Monte Carlo simulation of the renewal function

1981 ◽  
Vol 18 (2) ◽  
pp. 426-434 ◽  
Author(s):  
Mark Brown ◽  
Herbert Solomon ◽  
Michael A. Stephens
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Renewal Process ◽  
Time Distribution ◽  
Interarrival Time ◽  
Renewal Function ◽  
Expected Number ◽  
Unbiased Estimators ◽  
Monte Carlo Estimation ◽  
Naive Estimator

The problem of Monte Carlo estimation of M(t) = EN(t), the expected number of renewals in [0, t] for a renewal process with known interarrival time distribution F, is considered. Several unbiased estimators which compete favorably with the naive estimator, N(t), are presented and studied. An approach to reduce the variance of the Monte Carlo estimator is developed and illustrated.

Monte Carlo simulation of the renewal function

1981 ◽  
Vol 18 (02) ◽  
pp. 426-434 ◽  
Author(s):  
Mark Brown ◽  
Herbert Solomon ◽  
Michael A. Stephens
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Renewal Process ◽  
Time Distribution ◽  
Interarrival Time ◽  
Renewal Function ◽  
Expected Number ◽  
Unbiased Estimators ◽  
Monte Carlo Estimation ◽  
Naive Estimator

The problem of Monte Carlo estimation of M(t) = EN(t), the expected number of renewals in [0, t] for a renewal process with known interarrival time distribution F, is considered. Several unbiased estimators which compete favorably with the naive estimator, N(t), are presented and studied. An approach to reduce the variance of the Monte Carlo estimator is developed and illustrated.

Two results in the theory of queues

1970 ◽  
Vol 7 (01) ◽  
pp. 219-226 ◽  
Author(s):  
H. Ali
Keyword(s):  
Interarrival Time ◽  
Renewal Function ◽  
Expected Number

Summary In this paper it is shown that the distribution of the instant of service of a customer is symmetric as between the distributions of service and interarrival time. Also U(t), the expected number of departures in (0, t), is a delayed renewal function for the GI/M/1 queue.

scholarly journals The Estimation of Renewal Functions Using the Mean Value Theorem for Integrals (MeVTI) Method

d'CARTESIAN ◽  
2016 ◽  
Vol 5 (2) ◽  
pp. 111 ◽  
Author(s):  
Leopoldus Sasongko ◽  
Tundjung Mahatma
Keyword(s):  
Numerical Integration ◽  
Integral Equations ◽  
Integration Method ◽  
Mean Value ◽  
Mean Value Theorem ◽  
Time Interval ◽  
Renewal Function ◽  
Expected Number ◽  
Failure Distribution ◽  
The Mean

In the analysis of warranty, renewal functions are important in acquiring the expected number of failures of a nonrepairable component in a time interval. It is very difficult and complicated -if at all possible- to obtain a renewal function analytically. This paper proposes a numerical integration method for estimating renewal functions in the terms of renewal integral equations. The estimation is done through the Mean Value Theorem for Integrals (MeVTI) method after modifying the variable of the renewal integral equations. The accuracy of the estimation is measured by its comparison against the existing analytical approach of renewal functions, those are for Exponential, Erlang, Gamma, and Normal baseline failure distributions. The estimation of the renewal function for a Weibull baseline failure distribution as the results of the method is compared to that of the well-known numerical integration approaches, the Riemann-Stieljies and cubic spline methods. Keywords :    Mean Value Theorem for Integrals, Renewal Functions, Renewal Integral Equations.

RENEWAL PROCESS WITH FUZZY INTERARRIVAL TIMES AND REWARDS

2003 ◽  
Vol 11 (05) ◽  
pp. 573-586 ◽  
Author(s):  
RUIQING ZHAO ◽  
BAODING LIU
Keyword(s):  
Renewal Process ◽  
Interarrival Time ◽  
Renewal Theorem ◽  
Expected Number ◽  
Fuzzy Variables ◽  
Numerical Example ◽  
Interarrival Times ◽  
Renewal Reward Theorem

This paper considers a renewal process in which the interarrival times and rewards are characterized as fuzzy variables. A fuzzy elementary renewal theorem shows that the expected number of renewals per unit time is just the expected reciprocal of the interarrival time. Furthermore, the expected reward per unit time is provided by a fuzzy renewal reward theorem. Finally, a numerical example is presented for illustrating the theorems introduced in the paper.

On a Markovian queue with weakly correlated interarrival times

1981 ◽  
Vol 18 (01) ◽  
pp. 190-203 ◽  
Author(s):  
Guy Latouche
Keyword(s):  
Time Distribution ◽  
Queueing System ◽  
Interarrival Time ◽  
Probability Vector ◽  
Common Value ◽  
Markovian Queue ◽  
The Stability ◽  
Number Of Customers ◽  
Stationary Probabilities ◽  
Stationary Probability Vector

A queueing system with exponential service and correlated arrivals is analysed. Each interarrival time is exponentially distributed. The parameter of the interarrival time distribution depends on the parameter for the preceding arrival, according to a Markov chain. The parameters of the interarrival time distributions are chosen to be equal to a common value plus a factor ofε, where ε is a small number. Successive arrivals are then weakly correlated. The stability condition is found and it is shown that the system has a stationary probability vector of matrix-geometric form. Furthermore, it is shown that the stationary probabilities for the number of customers in the system, are analytic functions ofε, for sufficiently smallε, and depend more on the variability in the interarrival time distribution, than on the correlations.

scholarly journals The effect of change in population size on DNA polymorphism.

Genetics ◽  
1989 ◽  
Vol 123 (3) ◽  
pp. 597-601 ◽  
Author(s):  
F Tajima
Keyword(s):  
Population Size ◽  
Dna Sequences ◽  
Dna Polymorphism ◽  
Population Bottleneck ◽  
Expected Number ◽  
Original Population ◽  
Current Population ◽  
Segregating Sites

Abstract The expected number of segregating sites and the expectation of the average number of nucleotide differences among DNA sequences randomly sampled from a population, which is not in equilibrium, have been developed. The results obtained indicate that, in the case where the population size has changed drastically, the number of segregating sites is influenced by the size of the current population more strongly than is the average number of nucleotide differences, while the average number of nucleotide differences is affected by the size of the original population more severely than is the number of segregating sites. The results also indicate that the average number of nucleotide differences is affected by a population bottleneck more strongly than is the number of segregating sites.

Intercepting a Stealthy Network

2021 ◽  
Vol 17 (2) ◽  
pp. 1-39
Author(s):  
Mai Ben Adar Bessos ◽  
Amir Herzberg
Keyword(s):  
Mobile Devices ◽  
Short Range ◽  
Low Energy ◽  
Expected Number ◽  
Relay Communication

We investigate an understudied threat: networks of stealthy routers (S-Routers) , relaying messages to a hidden destination . The S-Routers relay communication along a path of multiple short-range, low-energy hops, to avoid remote localization by triangulation. Mobile devices called Interceptors can detect communication by an S-Router, but only when the Interceptor is next to the transmitting S-Router. We examine algorithms for a set of mobile Interceptors to find the destination of the communication relayed by the S-Routers. The algorithms are compared according to the number of communicating rounds before the destination is found, i.e., rounds in which data is transmitted from the source to the destination . We evaluate the algorithms analytically and using simulations, including against a parametric, optimized strategy for the S-Routers. Our main result is an Interceptors algorithm that bounds the expected number of communicating rounds by a term quasilinear in the number of S-Routers. For the case where S-Routers transmit at every round (“continuously”), we present an algorithm that improves this bound.

SET-VALUED PERFORMANCE APPROXIMATIONS FOR THE QUEUE GIVEN PARTIAL INFORMATION

2020 ◽  
pp. 1-23
Author(s):  
Yan Chen ◽  
Ward Whitt
Keyword(s):  
Steady State ◽  
Decay Rate ◽  
Waiting Time ◽  
Partial Information ◽  
Upper And Lower Bounds ◽  
Interarrival Time ◽  
Limited Information ◽  
Wide Range ◽  
The Mean ◽  
Third Moment

In order to understand queueing performance given only partial information about the model, we propose determining intervals of likely values of performance measures given that limited information. We illustrate this approach for the mean steady-state waiting time in the $GI/GI/K$ queue. We start by specifying the first two moments of the interarrival-time and service-time distributions, and then consider additional information about these underlying distributions, in particular, a third moment and a Laplace transform value. As a theoretical basis, we apply extremal models yielding tight upper and lower bounds on the asymptotic decay rate of the steady-state waiting-time tail probability. We illustrate by constructing the theoretically justified intervals of values for the decay rate and the associated heuristically determined interval of values for the mean waiting times. Without extra information, the extremal models involve two-point distributions, which yield a wide range for the mean. Adding constraints on the third moment and a transform value produces three-point extremal distributions, which significantly reduce the range, producing practical levels of accuracy.

scholarly journals Average Number of Nucleotide Differences in a Sample From a Single Subpopulation: A Test for Population Subdivision

Genetics ◽  
1987 ◽  
Vol 117 (1) ◽  
pp. 149-153
Author(s):  
Curtis Strobeck
Keyword(s):  
Monte Carlo Simulation ◽  
Population Structure ◽  
Random Mating ◽  
Population Subdivision ◽  
Expected Number ◽  
Migration Rates ◽  
Mating Population ◽  
Unbiased Estimates ◽  
Increasing Function ◽  
Stepping Stone Model

ABSTRACT Unbiased estimates of θ = 4Nµ in a random mating population can be based on either the number of alleles or the average number of nucleotide differences in a sample. However, if there is population structure and the sample is drawn from a single subpopulation, these two estimates of θ behave differently. The expected number of alleles in a sample is an increasing function of the migration rates, whereas the expected average number of nucleotide differences is shown to be independent of the migration rates and equal to 4N  Tµ for a general model of population structure which includes both the island model and the circular stepping-stone model. This contrast in the behavior of these two estimates of θ is used as the basis of a test for population subdivision. Using a Monte-Carlo simulation developed so that independent samples from a single subpopulation could be obtained quickly, this test is shown to be a useful method to determine if there is population subdivision.

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