Browsing by Subject "First passage time distribution"

Now showing 1 - 3 of 3

Open Access
Numerical methods for the transient analysis of multi-regime Markov fluid queues
(2019-01) Gürsoy, Ömer
Markov fluid queue models have served as one of the main tools for the performance analysis of computer and communication systems and networks. These models have also been used in other disciplines such as insurance risk, finance, inventory control, etc. This thesis focuses on the time dependent (transient) analysis of Markov uid queue models. In particular, a numerical method is proposed to obtain both the transient and first passage time distributions of a Multi-Regime Markov Fluid Queue (MRMFQ). The proposed method is based on obtaining the steady-state solution of an auxiliary MRMFQ that is to be constructed from the original MRMFQ which then leads to the related transient measures of interest. First, in order to model the deterministic time horizon, the Erlangization method is used. Then, as an alternative to Erlangization, ME-fication technique which efficiently replaces the Erlang distribution with a Concentrated Matrix Exponential (CME), is used. As an application of the proposed method, an M/M/S+G queue with generally distributed impatience times is modeled by using MRMFQs and our transient analysis method is subsequently applied to obtain the time dependent distributions. Numerical examples are given to show the effectiveness of the proposed transient analysis method while employing ME-fication.
Open Access
Steady-state and first passage time distributions for waiting times in the MAP/M/s+G queueing model with generally distributed patience times
(AIMS Press, 2022-11-30) Gürsoy, Ömer; Mehr, Kamal Adli; Akar, Nail
We study the MAP/M/s+G queueing model that arises in various multi-server engineering problems including telephone call centers, under the assumption of MAP (Markovian Arrival Process) arrivals, exponentially distributed service times, infinite waiting room, and generally distributed patience times. Using sample-path arguments, we propose to obtain the steady-state distribution of the virtual waiting time and subsequently the other relevant performance metrics of interest via the steady-state solution of a certain Continuous Feedback Fluid Queue (CFFQ). The proposed method is exact when the patience time is a discrete random variable and is asymptotically exact when it is continuous/hybrid, for which case discretization of the patience time distribution is required giving rise to a computational complexity depending linearly on the number of discretization levels. Additionally, a novel method is proposed to accurately obtain the first passage time distributions for the virtual and actual waiting times again using CFFQs while approximating the deterministic time horizons by Erlang distributions or more efficient Concentrated Matrix Exponential (CME) distributions. Numerical results are presented to validate the effectiveness of the proposed numerical method.
Open Access
Transient and first passage time distributions of first- and second-order Multi-Regime Markov Fluid Queues via ME-fication
(Springer, 2020) Akar, Nail; Gürsoy, Ömer; Horvath, G.; Telek, M.
We propose a numerical method to obtain the transient and first passage time distributions of first- and second-order Multi-Regime Markov Fluid Queues (MRMFQ). The method relies on the observation that these transient measures can be computed via the stationary analysis of an auxiliary MRMFQ. This auxiliary MRMFQ is constructed from the original one, using sample path arguments, and has a larger cardinality stemming from the need to keep track of time. The conventional method to approximately model the deterministic time horizon is Erlangization. As an alternative, we propose the so-called ME-fication technique, in which a Concentrated Matrix Exponential (CME) distribution replaces the Erlang distribution for approximating deterministic time horizons. ME-fication results in much lower state-space dimensionalities for the auxiliary MRMFQ than would be with Erlangization. Numerical results are presented to validate the effectiveness of ME-fication along with the proposed numerical method.