Stochastic comparisons for fork-join queues with exponential processing times

1997 ◽  
Vol 34 (2) ◽  
pp. 487-497 ◽  
Author(s):  
Esther Frostig ◽  
Tapani Lehtonen
Keyword(s):  
Random Variables ◽  
Single Server ◽  
Departure Process ◽  
Stochastic Comparisons ◽  
Processing Times ◽  
Service Rates ◽  
Service Times ◽  
Stochastic Majorization

Consider a fork-join queue, where each job upon arrival splits into k tasks and each joins a separate queue that is attended by a single server. Service times are independent, exponentially distributed random variables. Server i works at rate , where μ is constant. We prove that the departure process becomes stochastically faster as the service rates become more homogeneous in the sense of stochastic majorization. Consequently, when all k servers work with equal rates the departure process is stochastically maximized.

Stochastic comparisons for fork-join queues with exponential processing times

1997 ◽  
Vol 34 (02) ◽  
pp. 487-497 ◽  
Author(s):  
Esther Frostig ◽  
Tapani Lehtonen
Keyword(s):  
Random Variables ◽  
Single Server ◽  
Departure Process ◽  
Stochastic Comparisons ◽  
Processing Times ◽  
Service Rates ◽  
Service Times ◽  
Stochastic Majorization

Consider a fork-join queue, where each job upon arrival splits into k tasks and each joins a separate queue that is attended by a single server. Service times are independent, exponentially distributed random variables. Server i works at rate , where μ is constant. We prove that the departure process becomes stochastically faster as the service rates become more homogeneous in the sense of stochastic majorization. Consequently, when all k servers work with equal rates the departure process is stochastically maximized.

On the ordering of tandem queues with exponential servers

1986 ◽  
Vol 23 (01) ◽  
pp. 115-129 ◽  
Author(s):  
Tapani Lehtonen
Keyword(s):  
Service Time ◽  
Queueing System ◽  
Arrival Process ◽  
Single Server ◽  
Tandem Queues ◽  
Departure Process ◽  
Service Stations ◽  
Service Rates

We consider tandem queues which have a general arrival process. The queueing system consists of s (s ≧ 2) single-server service stations and the servers have exponential service-time distributions. Firstly we give a new proof for the fact that the departure process does not depend on the particular allocation of the servers to the stations. Secondly, considering the service rates, we prove that the departure process becomes stochastically faster as the homogeneity of the servers increases in the sense of a given condition. It turns out that, given the sum of the service rates, the departure process is stochastically fastest in the case where the servers are homogeneous.

On interchangeability for exponential single-server queues in tandem

1990 ◽  
Vol 27 (2) ◽  
pp. 459-464 ◽  
Author(s):  
Masaaki Kijima ◽  
Naoki Makimoto
Keyword(s):  
Direct Proof ◽  
Single Server ◽  
Tandem Queue ◽  
Exponential Distributions ◽  
Departure Process ◽  
Single Server Queues ◽  
Service Rates

Consider two exponential single-server queues in tandem and suppose that service rates of customer n are λ n and μ n respectively. In this note, a simple and direct proof is given of the fact that the departure process from the tandem queue is statistically unaffected when the service rates are interchanged if λ n – μn is independent of n. The proof is based only on the memoryless property of exponential distributions.

Queues with negative arrivals

1991 ◽  
Vol 28 (1) ◽  
pp. 245-250 ◽  
Author(s):  
Erol Gelenbe ◽  
Peter Glynn ◽  
Karl Sigman
Keyword(s):  
Stability Conditions ◽  
Queueing Models ◽  
Single Server ◽  
New Models ◽  
Service Rates ◽  
Service Times ◽  
The Stability ◽  
Negative Arrivals ◽  
The Way

We study single-server queueing models where in addition to regular arriving customers, there are negative arrivals. A negative arrival has the effect of removing a customer from the queue. The way in which this removal is specified gives rise to several different models. Unlike the standard FIFOGI/GI/1 model, the stability conditions for these new models may depend upon more than just the arrival and service rates; the entire distributions of interarrival and service times may be involved.

On the ordering of tandem queues with exponential servers

1986 ◽  
Vol 23 (1) ◽  
pp. 115-129 ◽  
Author(s):  
Tapani Lehtonen
Keyword(s):  
Service Time ◽  
Queueing System ◽  
Arrival Process ◽  
Single Server ◽  
Tandem Queues ◽  
Departure Process ◽  
Service Stations ◽  
Service Rates

We consider tandem queues which have a general arrival process. The queueing system consists of s (s ≧ 2) single-server service stations and the servers have exponential service-time distributions. Firstly we give a new proof for the fact that the departure process does not depend on the particular allocation of the servers to the stations. Secondly, considering the service rates, we prove that the departure process becomes stochastically faster as the homogeneity of the servers increases in the sense of a given condition. It turns out that, given the sum of the service rates, the departure process is stochastically fastest in the case where the servers are homogeneous.

On interchangeability for exponential single-server queues in tandem

1990 ◽  
Vol 27 (02) ◽  
pp. 459-464 ◽  
Author(s):  
Masaaki Kijima ◽  
Naoki Makimoto
Keyword(s):  
Direct Proof ◽  
Single Server ◽  
Tandem Queue ◽  
Exponential Distributions ◽  
Departure Process ◽  
Single Server Queues ◽  
Service Rates

Consider two exponential single-server queues in tandem and suppose that service rates of customer n are λ n and μ n respectively. In this note, a simple and direct proof is given of the fact that the departure process from the tandem queue is statistically unaffected when the service rates are interchanged if λ n – μn is independent of n. The proof is based only on the memoryless property of exponential distributions.

Queues with negative arrivals

1991 ◽  
Vol 28 (01) ◽  
pp. 245-250 ◽  
Author(s):  
Erol Gelenbe ◽  
Peter Glynn ◽  
Karl Sigman
Keyword(s):  
Stability Conditions ◽  
Queueing Models ◽  
Single Server ◽  
New Models ◽  
Service Rates ◽  
Service Times ◽  
The Stability ◽  
Negative Arrivals ◽  
The Way

We study single-server queueing models where in addition to regular arriving customers, there are negative arrivals. A negative arrival has the effect of removing a customer from the queue. The way in which this removal is specified gives rise to several different models. Unlike the standard FIFO GI/GI/1 model, the stability conditions for these new models may depend upon more than just the arrival and service rates; the entire distributions of interarrival and service times may be involved.

scholarly journals A Taylor Series Approach for Service-Coupled Queueing Systems with Intermediate Load

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Ekaterina Evdokimova ◽  
Sabine Wittevrongel ◽  
Dieter Fiems
Keyword(s):  
Performance Measures ◽  
Queueing Systems ◽  
Poisson Processes ◽  
Series Expansions ◽  
Service Rate ◽  
Single Server ◽  
Queueing Model ◽  
State Space Explosion ◽  
Finite Queues ◽  
Service Rates

This paper investigates the performance of a queueing model with multiple finite queues and a single server. Departures from the queues are synchronised or coupled which means that a service completion leads to a departure in every queue and that service is temporarily interrupted whenever any of the queues is empty. We focus on the numerical analysis of this queueing model in a Markovian setting: the arrivals in the different queues constitute Poisson processes and the service times are exponentially distributed. Taking into account the state space explosion problem associated with multidimensional Markov processes, we calculate the terms in the series expansion in the service rate of the stationary distribution of the Markov chain as well as various performance measures when the system is (i) overloaded and (ii) under intermediate load. Our numerical results reveal that, by calculating the series expansions of performance measures around a few service rates, we get accurate estimates of various performance measures once the load is above 40% to 50%.

scholarly journals Stochastic Comparisons of Some Distances between Random Variables

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 981
Author(s):  
Patricia Ortega-Jiménez ◽  
Miguel A. Sordo ◽  
Alfonso Suárez-Llorens
Keyword(s):  
Financial Risk ◽  
Sufficient Conditions ◽  
Random Variables ◽  
Stochastic Ordering ◽  
Random Variable ◽  
Distribution Functions ◽  
Stochastic Comparisons ◽  
Stochastic Orderings ◽  
Absolute Value ◽  
The Difference

The aim of this paper is twofold. First, we show that the expectation of the absolute value of the difference between two copies, not necessarily independent, of a random variable is a measure of its variability in the sense of Bickel and Lehmann (1979). Moreover, if the two copies are negatively dependent through stochastic ordering, this measure is subadditive. The second purpose of this paper is to provide sufficient conditions for comparing several distances between pairs of random variables (with possibly different distribution functions) in terms of various stochastic orderings. Applications in actuarial and financial risk management are given.

On a tandem queueing model with identical service times at both counters, I

1979 ◽  
Vol 11 (3) ◽  
pp. 616-643 ◽  
Author(s):  
O. J. Boxma
Keyword(s):  
Waiting Times ◽  
Sufficient Conditions ◽  
Complete Analysis ◽  
Single Server ◽  
Stationary Distributions ◽  
In Series ◽  
Queues In Series ◽  
Service Times ◽  
Necessary And Sufficient ◽  
Insight Into

This paper considers a queueing system consisting of two single-server queues in series, in which the service times of an arbitrary customer at both queues are identical. Customers arrive at the first queue according to a Poisson process.Of this model, which is of importance in modern network design, a rather complete analysis will be given. The results include necessary and sufficient conditions for stationarity of the tandem system, expressions for the joint stationary distributions of the actual waiting times at both queues and of the virtual waiting times at both queues, and explicit expressions (i.e., not in transform form) for the stationary distributions of the sojourn times and of the actual and virtual waiting times at the second queue.In Part II (pp. 644–659) these results will be used to obtain asymptotic and numerical results, which will provide more insight into the general phenomenon of tandem queueing with correlated service times at the consecutive queues.

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