scholarly journals Simulation-Based Computation of the Workload Correlation Function in a Lévy-Driven Queue

2011 ◽  
Vol 48 (1) ◽  
pp. 114-130 ◽  
Author(s):  
Peter W. Glynn ◽  
Michel Mandjes
Keyword(s):  
Correlation Function ◽  
Variance Reduction ◽  
Single Server ◽  
Monotone Functions ◽  
Single Server Queue ◽  
Completely Monotone Functions ◽  
Simulation Techniques ◽  
Completely Monotone ◽  
Simulation Based ◽  
Server Queue

In this paper we consider a single-server queue with Lévy input, and, in particular, its workload process (Qt)t≥0, focusing on its correlation structure. With the correlation function defined asr(t):= cov(Q0,Qt) / varQ0(assuming that the workload process is in stationarity at time 0), we first study its transform ∫0∞r(t)e-ϑtdt, both for when the Lévy process has positive jumps and when it has negative jumps. These expressions allow us to prove thatr(·) is positive, decreasing, and convex, relying on the machinery of completely monotone functions. For the light-tailed case, we estimate the behavior ofr(t) for larget. We then focus on techniques to estimater(t) by simulation. Naive simulation techniques require roughly (r(t))-2runs to obtain an estimate of a given precision, but we develop a coupling technique that leads to substantial variance reduction (the required number of runs being roughly (r(t))-1). If this is augmented with importance sampling, it even leads to a logarithmically efficient algorithm.

scholarly journals Simulation-Based Computation of the Workload Correlation Function in a Lévy-Driven Queue

2011 ◽  
Vol 48 (01) ◽  
pp. 114-130 ◽  
Author(s):  
Peter W. Glynn ◽  
Michel Mandjes
Keyword(s):  
Correlation Function ◽  
Variance Reduction ◽  
Single Server ◽  
Monotone Functions ◽  
Single Server Queue ◽  
Completely Monotone Functions ◽  
Simulation Techniques ◽  
Completely Monotone ◽  
Simulation Based ◽  
Server Queue

In this paper we consider a single-server queue with Lévy input, and, in particular, its workload process (Q t ) t≥0, focusing on its correlation structure. With the correlation function defined as r(t):= cov(Q 0, Q t ) / varQ 0 (assuming that the workload process is in stationarity at time 0), we first study its transform ∫0 ∞ r(t)e-ϑt dt, both for when the Lévy process has positive jumps and when it has negative jumps. These expressions allow us to prove that r(·) is positive, decreasing, and convex, relying on the machinery of completely monotone functions. For the light-tailed case, we estimate the behavior of r(t) for large t. We then focus on techniques to estimate r(t) by simulation. Naive simulation techniques require roughly (r(t))-2 runs to obtain an estimate of a given precision, but we develop a coupling technique that leads to substantial variance reduction (the required number of runs being roughly (r(t))-1). If this is augmented with importance sampling, it even leads to a logarithmically efficient algorithm.

scholarly journals On the Correlation Structure of a Lévy-Driven Queue

2008 ◽  
Vol 45 (4) ◽  
pp. 940-952 ◽  
Author(s):  
Abdelghafour Es-Saghouani ◽  
Michel Mandjes
Keyword(s):  
Random Variable ◽  
Correlation Structure ◽  
Single Server ◽  
Monotone Functions ◽  
Single Server Queue ◽  
Completely Monotone Functions ◽  
Complementary Distribution ◽  
Completely Monotone ◽  
Server Queue ◽  
Heavy Tailed

In this paper we consider a single-server queue with Lévy input and, in particular, its workload process (Qt)t≥0, with a focus on the correlation structure. With the correlation function defined asr(t) := cov(Q0,Qt) / var(Q0) (assuming that the workload process is in stationarity at time 0), we first determine its transform ∫0∞r(t)e-ϑtdt. This expression allows us to prove thatr(·) is positive, decreasing, and convex, relying on the machinery of completely monotone functions. We also show thatr(·) can be represented as the complementary distribution function of a specific random variable. These results are used to compute the asymptotics ofr(t), for larget, for the cases of light-tailed and heavy-tailed Lévy inputs.

scholarly journals On the Correlation Structure of a Lévy-Driven Queue

2008 ◽  
Vol 45 (04) ◽  
pp. 940-952 ◽  
Author(s):  
Abdelghafour Es-Saghouani ◽  
Michel Mandjes
Keyword(s):  
Random Variable ◽  
Correlation Structure ◽  
Single Server ◽  
Monotone Functions ◽  
Single Server Queue ◽  
Completely Monotone Functions ◽  
Complementary Distribution ◽  
Completely Monotone ◽  
Server Queue ◽  
Heavy Tailed

In this paper we consider a single-server queue with Lévy input and, in particular, its workload process (Q t ) t≥0, with a focus on the correlation structure. With the correlation function defined as r(t) := cov(Q 0, Q t ) / var(Q 0) (assuming that the workload process is in stationarity at time 0), we first determine its transform ∫0 ∞ r(t)e-ϑt dt. This expression allows us to prove that r(·) is positive, decreasing, and convex, relying on the machinery of completely monotone functions. We also show that r(·) can be represented as the complementary distribution function of a specific random variable. These results are used to compute the asymptotics of r(t), for large t, for the cases of light-tailed and heavy-tailed Lévy inputs.

The single-server queue with service depending on queue size and with the preemptive-resume last-come–first-served queue discipline

1987 ◽  
Vol 24 (03) ◽  
pp. 758-767
Author(s):  
D. Fakinos
Keyword(s):  
Queueing System ◽  
Limiting Distribution ◽  
Single Server ◽  
Queue Size ◽  
Single Server Queue ◽  
Preemptive Resume ◽  
Server Queue ◽  
Queue Discipline ◽  
Service Times

This paper studies theGI/G/1 queueing system assuming that customers have service times depending on the queue size and also that they are served in accordance with the preemptive-resume last-come–first-served queue discipline. Expressions are given for the limiting distribution of the queue size and the remaining durations of the corresponding services, when the system is considered at arrival epochs, at departure epochs and continuously in time. Also these results are applied to some particular cases of the above queueing system.

scholarly journals New Approach for Finding Basic Performance Measures of Single Server Queue

2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Siew Khew Koh ◽  
Ah Hin Pooi ◽  
Yi Fei Tan
Keyword(s):  
Stationary State ◽  
Queue Length ◽  
Length Distribution ◽  
Cumulative Distribution ◽  
System Capacity ◽  
Interarrival Time ◽  
Single Server ◽  
Single Server Queue ◽  
Queue Length Distribution ◽  
Server Queue

Consider the single server queue in which the system capacity is infinite and the customers are served on a first come, first served basis. Suppose the probability density functionf(t)and the cumulative distribution functionF(t)of the interarrival time are such that the ratef(t)/1-F(t)tends to a constant ast→∞, and the rate computed from the distribution of the service time tends to another constant. When the queue is in a stationary state, we derive a set of equations for the probabilities of the queue length and the states of the arrival and service processes. Solving the equations, we obtain approximate results for the stationary probabilities which can be used to obtain the stationary queue length distribution and waiting time distribution of a customer who arrives when the queue is in the stationary state.

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