Markovian Random Environment Research Articles

Transmission Dynamics of a High Dimensional Rabies Epidemic Model in a Markovian Random Environment

Transmission Dynamics of a High Dimensional Rabies Epidemic Model in a Markovian Random Environment

The Queueing Model MAP|PH|1|N with Feedback Operating in a Markovian Random Environment

Queueing systems with feedback are well suited for the description of message transmission and manufacturing processes where a repeated service is required. In the present paper we investigate a rather general single server queue with a Markovian Arrival Process (MAP), Phase-type (PH) service-time distribution, a finite buffer and feedback which operates in a random environment. A finite state Markovian random environment affects the parameters of the input and service processes and the feedback probability. The stationary distribution of the queue and of the sojourn times as well as the loss probability are calculated. Moreover, Little’s law is derived.

Lyapunov Exponents for Branching Processes in a Random Environment: The Effect of Information

We consider multitype branching processes evolving in a Markovian random environment. To determine whether or not the branching process becomes extinct almost surely is akin to computing the maximal Lyapunov exponent of a sequence of random matrices, which is a notoriously difficult problem. We define Markov chains associated to the branching process, and we construct bounds for the Lyapunov exponent. The bounds are obtained by adding or by removing information: to add information results in a lower bound, to remove information results in an upper bound, and we show that adding less information improves the lower bound. We give a few illustrative examples and we observe that the upper bound is generally more accurate than the lower bounds.

BMAP<sup>(r)</sup>/M<sup>(r)</sup>/N<sup>(r)</sup> 대기행렬시스템 분석

A multi-server queueing system with an infinite buffer and impatient customers is analyzed. The system operates in the finite state Markovian random environment. The number of available servers, the parameters of the batch Markovian arrival process, the rate of customers’ service, and the impatience intensity depend on the current state of the random environment and immediately change their values at the moments of jumps of the random environment. Dynamics of the system is described by the multi-dimensional asymptotically quasi-Toeplitz Markov chain. The ergodicity condition is derived. The main performance measures of the system are calculated. Numerical results are presented.

The deterministic SIS epidemic model in a Markovian random environment.

We consider the classical deterministic susceptible-infective-susceptible epidemic model, where the infection and recovery rates depend on a background environmental process that is modeled by a continuous time Markov chain. This framework is able to capture several important characteristics that appear in the evolution of real epidemics in large populations, such as seasonality effects and environmental influences. We propose computational approaches for the determination of various distributions that quantify the evolution of the number of infectives in the population.

Priority retrial queueing model operating in random environment with varying number and reservation of servers

We consider a multi-server queueing system with two types of customers operating in the Markovian random environment. Under the fixed state of the random environment, the arrival flow is described by the marked Markovian arrival process. Type 1 customers have preemptive priority over type 2 customers. Type 1 customer is lost only if, at its arrival moment, all servers are busy by type 1 customers. The service times of both types of customers have an exponential distribution with the rate depending on the type of a customer. Type 2 customer is accepted for service if the number of busy servers at its arrival epoch does not exceed a fixed threshold. Otherwise, the arriving customer makes a randomized choice to leave the system permanently (to balk) or to join so called orbit and try to obtain service later. The inter-retrial times have an exponential distribution. Customers in orbit can be impatient and may leave the system after an exponentially distributed amount of time. Due to preemptive priority of type 1 customers, service of type 2 customer can be interrupted. In this case, the interrupted customer makes a randomized choice to leave the system permanently or go into orbit. When the random environment changes its state, immediately the following parameters of the system change their value: the total number of servers, the number of servers available for type 2 customers, the matrices defining the arrival process, the rates of service of customers, the rate of retrials, the impatience intensity, the probability of balking the system at the arrival moment or the moment of termination of service of type 2 customer. Behavior of the system is described by the level dependent multi-dimensional Markov chain that belongs to the class of asymptotically quasi-Toeplitz Markov chains. This allows us to derive the ergodicity condition for this Markov chain and compute its stationary distribution. The main performance measures of the system are expressed via the stationary state probabilities. Numerical illustrations are presented.

A Structured Markov Chain Approach to Branching Processes

Algorithmic methods developed for structured Markov chains are extended to solve questions about a class of continuous-time branching processes called Markovian binary trees (MBTs). This approach allows us to compute the extinction probability of an MBT, the distribution of its maximal size given extinction, the expected time until extinction, and the mean time until the tree reaches a given size. The resulting algorithms are efficient in practice for processes of relatively small dimension. The numerical methods are illustrated on MBTs evolving in a Markovian random environment.

The MAP/PH/N retrial queue in a random environment

We consider the MAP/PH/N retrial queue with a finite number of sources operating in a finite state Markovian random environment. Two different types of multi-dimensional Markov chains are investigated describing the behavior of the system based on state space arrangements. The special features of the two formulations are discussed. The algorithms for calculating the stationary state probabilities are elaborated, based on which the main performance measures are obtained, and numerical examples are presented as well.

Analysis of the finite source MAP/PH/N retrial G-queue operating in a random environment

Finite source retrial G-queues are good mathematical models of communication systems and networks, so their investigation is important for theory and applications. In this paper, we analyze the MAP/PH/N retrial queue with finite number of sources and MAP arrivals of negative customers operating in a finite state Markovian random environment. The arrival of a negative customer with equal probability goes to any busy server to remove the customer being in service. The multi-dimensional Markov chain describing the behavior of the system is investigated. The algorithms for calculating the stationary state probabilities are elaborated. Main performance measures are obtained. Illustrative numerical examples are presented.

The survival probability of a critical branching process in a Markovian random environment

In this Note, we first prove a local limit theorem for a semi-Markov chain and then apply it to study the asymptotic behavior of the survival probability of a critical branching process in Markovian random environment.

Queues with slow servers and impatient customers

Abstract We study M / M / c queues ( c = 1 , 1 c ∞ and c = ∞ ) in a 2-phase (fast and slow) Markovian random environment, with impatient customers. The system resides in the fast phase (phase 1) an exponentially distributed random time with parameter η and the arrival and service rates are λ and μ, respectively. The corresponding parameters for the slow phase (phase 0) are γ, λ 0 , and μ 0 ( ⩽ μ ) . When in the slow phase, customers become impatient. That is, each customer, upon arrival, activates an individual timer, exponentially distributed with parameter ξ. If the system does not change its environment from 0 to 1 before the customer’s timer expires, the customer abandons the queue never to return. We concentrate on deriving analytic solutions to the queue-length distributions. We derive, for each case of c, the corresponding probability generating function, and calculate the mean queue size. Several extreme cases are investigated and numerical results are presented.

The BMAP/ PH/ N retrial queueing system operating in Markovian random environment

We consider the BMAP/ PH/ N retrial queueing system operating in a finite state space Markovian random environment. The stationary distribution of the system states is computed. The main performance measures of the system are derived. Presented numerical examples illustrate a poor quality of the approximation of the main performance measures of the system by means of the simpler queueing models. An effect of smoothing the traffic and an impact of intensity of retrials are shown.

Erlang loss queueing system with batch arrivals operating in a random environment

We consider the BMAP / PH / N / 0 queueing system operating in a finite state space Markovian random environment. Disciplines of partial admission, complete rejection and complete admission are analyzed. The stationary distribution of the system states is calculated. The loss probability and other main performance measures of the system are derived. The Laplace–Stieltjes transform of the sojourn time distribution of accepted customers is obtained. Illustrative numerical examples are presented. They show effect of an admission strategy, a correlation in an arrival process, a variation of a service process. Poor quality of the loss probability approximation by means of more simple models utilization is illustrated.

The [formula omitted] retrial queueing system operating in random environment

A single-server retrial queueing model with the batch Markovian arrival process and phase-type service time distribution is analyzed. The system has R operation modes which are switched by a Markovian random environment. The multi-dimensional Markov chain describing the behavior of the system is investigated by means of continuous time asymptotically quasi-toeplitz Markov chains. It allows to obtain a constructive form ergodicity condition and elaborate stable algorithms for calculating the stationary distribution. Main performance measures are computed. Numerical illustrations are presented.

A FLUID EOQ MODEL WITH A TWO-STATE RANDOM ENVIRONMENT

We study a stochastic fluid EOQ-type model operating in a Markovian random environment of alternating good and bad periods determining the demand rate. We deal with the classical problem of “when to place an order” and “how big it should be,” leading to the trade-off between the setup cost and the holding cost. The key functionals are the steady-state mean of the content level, the expected cycle length (which is the time between two large orders), and the expected number of orders in a cycle. These performance measures are derived in closed form by using the level crossing approach in an intricate way. We also present numerical examples and carry out a sensitivity analysis.

One-dimensional branching random walks in a Markovian random environment

We study a one-dimensional supercritical branching random walk in a non-i.i.d. random environment, which considers both the branching mechanism and the step transition. This random environment is constructed using a recurrent Markov chain on a finite or countable state space. Criteria of (strong) recurrence and transience are presented for this model.

One-dimensional branching random walks in a Markovian random environment

We study a one-dimensional supercritical branching random walk in a non-i.i.d. random environment, which considers both the branching mechanism and the step transition. This random environment is constructed using a recurrent Markov chain on a finite or countable state space. Criteria of (strong) recurrence and transience are presented for this model.

Service networks with multichannel nodes in a random environment

Service networks with multichannel nodes of semi-Markovian type are considered. The parameters of a source of demands depend on the state of the Markovian random environment. For the process of servicing demands, the conditions of existence of a stationary mode are found, and the properties of stationary distribution in terms of spectral characteristics of the routing matrix are investigated.

Transition phenomena for a Galton-Watson process with immigration in a Markovian environment

The behavior of a Galton-Watson process with state-dependent immigration in a Markovian random environment is investigated. We obtain a limit theorem in the near-critical case.