Busy-period analysis of a correlated queue with exponential demand and service

1987 ◽  
Vol 24 (02) ◽  
pp. 476-485 ◽  
Author(s):  
Christos Langaris
Keyword(s):  
Probability Density Function ◽  
Busy Period ◽  
Joint Probability ◽  
Closed Form Expression ◽  
Single Server ◽  
Form Expression ◽  
Period Analysis ◽  
The Laplace Transform ◽  
Number Of Customers ◽  
Period Duration

In this paper we investigate the server's busy period in a single-server queueing situation in which the interarrival interval T preceding the arrival of a customer and his service time S are assumed correlated. A closed-form expression is obtained for the Laplace transform bn (z) of the joint probability and probability density function of the busy period duration and the number of customers served in it. Some numerical values are given showing the effect of correlation between T and S.

Busy-period analysis of a correlated queue with exponential demand and service

1987 ◽  
Vol 24 (2) ◽  
pp. 476-485 ◽  
Author(s):  
Christos Langaris
Keyword(s):  
Probability Density Function ◽  
Busy Period ◽  
Joint Probability ◽  
Closed Form Expression ◽  
Single Server ◽  
Form Expression ◽  
Period Analysis ◽  
The Laplace Transform ◽  
Number Of Customers ◽  
Period Duration

In this paper we investigate the server's busy period in a single-server queueing situation in which the interarrival interval T preceding the arrival of a customer and his service time S are assumed correlated. A closed-form expression is obtained for the Laplace transform bn(z) of the joint probability and probability density function of the busy period duration and the number of customers served in it. Some numerical values are given showing the effect of correlation between T and S.

The generalised state-dependent queue: the busy period Erlangian

1974 ◽  
Vol 11 (03) ◽  
pp. 618-623
Author(s):  
B. W. Conolly
Keyword(s):  
Laplace Transform ◽  
Generating Function ◽  
Busy Period ◽  
Continued Fraction ◽  
Queueing System ◽  
Joint Probability ◽  
Single Server ◽  
System State ◽  
State Dependent ◽  
The Laplace Transform

A continued fraction representation is presented of the Laplace transform of the generating function of the fundamental joint probability and density of busy period length measured in customers served and duration in time. The setting is the single server Erlang queueing system where the parameters of negative exponentially distributed arrival and service times have a general dependence on instantaneous system state.

scholarly journals Analysis of polling models with a self-ruling server

2019 ◽  
Vol 94 (1-2) ◽  
pp. 77-107 ◽  
Author(s):  
Jan-Kees van Ommeren ◽  
Ahmad Al Hanbali ◽  
Richard J. Boucherie
Keyword(s):  
Probability Generating Function ◽  
Joint Probability ◽  
Polling Systems ◽  
Single Server ◽  
Batch Arrivals ◽  
Exponential Time ◽  
Polling Models ◽  
The Laplace Transform ◽  
Expected Sojourn Time ◽  
Number Of Customers

AbstractPolling systems are systems consisting of multiple queues served by a single server. In this paper, we analyze polling systems with a server that is self-ruling, i.e., the server can decide to leave a queue, independent of the queue length and the number of served customers, or stay longer at a queue even if there is no customer waiting in the queue. The server decides during a service whether this is the last service of the visit and to leave the queue afterward, or it is a regular service followed, possibly, by other services. The characteristics of the last service may be different from the other services. For these polling systems, we derive a relation between the joint probability generating functions of the number of customers at the start of a server visit and, respectively, at the end of a server visit. We use these key relations to derive the joint probability generating function of the number of customers and the Laplace transform of the workload in the queues at an arbitrary time. Our analysis in this paper is a generalization of several models including the exponential time-limited model with preemptive-repeat-random service, the exponential time-limited model with non-preemptive service, the gated time-limited model, the Bernoulli time-limited model, the 1-limited discipline, the binomial gated discipline, and the binomial exhaustive discipline. Finally, we apply our results on an example of a new polling discipline, called the 1 + 1 self-ruling server, with Poisson batch arrivals. For this example, we compute numerically the expected sojourn time of an arbitrary customer in the queues.

The generalised state-dependent queue: the busy period Erlangian

1974 ◽  
Vol 11 (3) ◽  
pp. 618-623 ◽  
Author(s):  
B. W. Conolly
Keyword(s):  
Laplace Transform ◽  
Generating Function ◽  
Busy Period ◽  
Continued Fraction ◽  
Queueing System ◽  
Joint Probability ◽  
Single Server ◽  
System State ◽  
State Dependent ◽  
The Laplace Transform

A continued fraction representation is presented of the Laplace transform of the generating function of the fundamental joint probability and density of busy period length measured in customers served and duration in time. The setting is the single server Erlang queueing system where the parameters of negative exponentially distributed arrival and service times have a general dependence on instantaneous system state.

Distribution of Consensus in a Broadcasting-based Consensus-forming Algorithm

2021 ◽  
Vol 48 (3) ◽  
pp. 91-96
Author(s):  
Shigeo Shioda
Keyword(s):  
Distribution Function ◽  
Probability Density Function ◽  
Closed Form ◽  
Probability Density ◽  
Infinite Number ◽  
Stable Distribution ◽  
Random Variable ◽  
Cauchy Distribution ◽  
Closed Form Expression ◽  
Form Expression

The consensus achieved in the consensus-forming algorithm is not generally a constant but rather a random variable, even if the initial opinions are the same. In the present paper, we investigate the statistical properties of the consensus in a broadcasting-based consensus-forming algorithm. We focus on two extreme cases: consensus forming by two agents and consensus forming by an infinite number of agents. In the two-agent case, we derive several properties of the distribution function of the consensus. In the infinite-numberof- agents case, we show that if the initial opinions follow a stable distribution, then the consensus also follows a stable distribution. In addition, we derive a closed-form expression of the probability density function of the consensus when the initial opinions follow a Gaussian distribution, a Cauchy distribution, or a L´evy distribution.

The Trivariate Distribution of the Maximum Queue Length, the Number of Customers Served and the Duration of the Busy Period for the M/G/1 Queueing System

1969 ◽  
Vol 6 (1) ◽  
pp. 154-161 ◽  
Author(s):  
E.G. Enns
Keyword(s):  
Queue Length ◽  
Busy Period ◽  
Queueing System ◽  
Single Server ◽  
List Type ◽  
Type Number ◽  
Distribution Of The Maximum ◽  
Maximum Queue Length ◽  
Number Of Customers

In the study of the busy period for a single server queueing system, three variables that have been investigated individually or at most in pairs are:1.The duration of the busy period.2.The number of customers served during the busy period.3.The maximum number of customers in the queue during the busy period.

q-SERIES IN MARKOV CHAINS WITH BINOMIAL TRANSITIONS

2008 ◽  
Vol 23 (1) ◽  
pp. 75-99 ◽  
Author(s):  
Antonis Economou ◽  
Stella Kapodistria
Keyword(s):  
Busy Period ◽  
Hypergeometric Series ◽  
Binomial Coefficients ◽  
Single Server ◽  
Transition Rates ◽  
Extensive Analysis ◽  
Service Completion ◽  
Markovian Queue ◽  
Number Of Customers ◽  
Sojourn Time Distributions

We consider a single-server Markovian queue with synchronized services and setup times. The customers arrive according to a Poisson process and are served simultaneously. The service times are independent and exponentially distributed. At a service completion epoch, every customer remains satisfied with probability p (independently of the others) and departs from the system; otherwise, he stays for a new service. Moreover, the server takes multiple vacations whenever the system is empty.Some of the transition rates of the underlying two-dimensional Markov chain involve binomial coefficients dependent on the number of customers. Indeed, at each service completion epoch, the number of customers n is reduced according to a binomial (n, p) distribution. We show that the model can be efficiently studied using the framework of q-hypergeometric series and we carry out an extensive analysis including the stationary, the busy period, and the sojourn time distributions. Exact formulas and numerical results show the effect of the level of synchronization to the performance of such systems.

scholarly journals A Perishable Inventory System with Postponed Demands and Multiple Server Vacations

2012 ◽  
Vol 2012 ◽  
pp. 1-17 ◽  
Author(s):  
R. Jayaraman ◽  
B. Sivakumar ◽  
G. Arivarignan
Keyword(s):  
Steady State ◽  
Joint Probability ◽  
Life Time ◽  
Inventory System ◽  
Inventory Level ◽  
Joint Probability Distribution ◽  
Single Server ◽  
Cost Rate ◽  
Stochastic Inventory ◽  
Number Of Customers

A mathematical modelling of a continuous review stochastic inventory system with a single server is carried out in this work. We assume that demand time points form a Poisson process. The life time of each item is assumed to have exponential distribution. We assume(s,S)ordering policy to replenish stock with random lead time. The server goes for a vacation of an exponentially distributed duration at the time of stock depletion and may take subsequent vacation depending on the stock position. The customer who arrives during the stock-out period or during the server vacation is offered a choice of joining a pool which is of finite capacity or leaving the system. The demands in the pool are selected one by one by the server only when the inventory level is aboves, with interval time between any two successive selections distributed as exponential with parameter depending on the number of customers in the pool. The joint probability distribution of the inventory level and the number of customers in the pool is obtained in the steady-state case. Various system performance measures in the steady state are derived, and the long-run total expected cost rate is calculated.

scholarly journals Explicit results for the distribution of the number of customers served during a busy period for $M^X/PH/1$ queue

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Veena Goswami ◽  
M. L. Chaudhry
Keyword(s):  
Functional Equation ◽  
Busy Period ◽  
Stochastic Modelling ◽  
Lagrange Inversion ◽  
Special Cases ◽  
Service Distribution ◽  
Phase Type ◽  
Phase Type Distributions ◽  
The Laplace Transform ◽  
Number Of Customers

<p style='text-indent:20px;'>We give analytically explicit solutions for the distribution of the number of customers served during a busy period for the <inline-formula><tex-math id="M1">\begin{document}$ M^X/PH/1 $\end{document}</tex-math></inline-formula> queues when initiated with <inline-formula><tex-math id="M2">\begin{document}$ m $\end{document}</tex-math></inline-formula> customers. When customers arrive in batches, we present the functional equation for the Laplace transform of the number of customers served during a busy period. Applying the Lagrange inversion theorem, we provide a refined result to this functional equation. From a phase-type service distribution, we obtain the distribution of the number of customers served during a busy period for various special cases such as exponential, Erlang-k, generalized Erlang, hyperexponential, Coxian, and interrupted Poisson process. The results are exact, rapid and vigorous, owing to the clarity of the expressions. Moreover, we also consider computational results for several service-time distributions using our method. Phase-type distributions can approximate any non-negative valued distribution arbitrarily close, making them a useful practical stochastic modelling tool. These distributions have eloquent properties which make them beneficial in the computation of performance models.</p>

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.

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