scholarly journals Analysis of Single-Server Queue with Phase-Type Service and Energy Harvesting

2016 ◽  
Vol 2016 ◽  
pp. 1-16 ◽  
Author(s):  
Sergey A. Dudin ◽  
Moon Ho Lee
Keyword(s):  
Sensor Node ◽  
Random Number ◽  
Single Server ◽  
Finite Capacity ◽  
Central Node ◽  
Phase Type ◽  
Server Queue ◽  
Arrival Processes ◽  
System States ◽  
Little's Formula

We propose a queueing model suitable, for example, for modelling operation of nodes of sensor networks. The sensor node senses a random field and generates packets to be transmitted to the central node. The sensor node has a battery of a finite capacity and harvests energy during its operation from outside (using solar cells, wind turbines, piezoelectric cells, etc.). We assume that, generally speaking, service (transmission) of a packet consists of a random number of phases and implementation of each phase requires a unit of energy. If the battery becomes empty, transmission is failed. To reduce the probability of forced transmission termination, we suggest that the packet can be accepted for transmission only when the number of energy units is greater than or equal to some threshold. Under quite general assumptions about the pattern of the arrival processes of packets and energy, we compute the stationary distributions of the system states and the waiting time of a packet in the system and numerically analyze performance measures of the system as functions of the threshold. Validity of Little’s formula and its counterpart is verified.

A single-server queue with server vacations and a class of non-renewal arrival processes

1990 ◽  
Vol 22 (3) ◽  
pp. 676-705 ◽  
Author(s):  
David M. Lucantoni ◽  
Kathleen S. Meier-Hellstern ◽  
Marcel F. Neuts
Keyword(s):  
Waiting Times ◽  
Arrival Process ◽  
Single Server ◽  
Single Server Queue ◽  
Arbitrary Time ◽  
Markov Modulated Poisson Process ◽  
Special Cases ◽  
Server Queue ◽  
Arrival Processes ◽  
Markov Modulated

We study a single-server queue in which the server takes a vacation whenever the system becomes empty. The service and vacation times and the arrival process are all assumed to be mutually independent. The successive service times and the vacation times each form independent, identically distributed sequences with general distributions. A new class of non-renewal arrival processes is introduced. As special cases, it includes the Markov-modulated Poisson process and the superposition of phase-type renewal processes.Algorithmically tractable equations for the distributions of the waiting times at an arbitrary time and at arrivals, as well as for the queue length at an arbitrary time, at arrivals, and at departures are established. Some factorizations, which are known for the case of renewal input, are generalized to this new framework and new factorizations are obtained. The algorithmic implementation of these results is discussed.

Exponential expansion for the tail of the waiting-time probability in the single-server queue with batch arrivals

1988 ◽  
Vol 20 (4) ◽  
pp. 880-895 ◽  
Author(s):  
J. C. W. Van Ommeren
Keyword(s):  
Waiting Time ◽  
Interarrival Time ◽  
Single Server ◽  
Waiting Time Distribution ◽  
Single Server Queue ◽  
Batch Arrivals ◽  
Exponential Expansion ◽  
Phase Type ◽  
Phase Type Distributions ◽  
Server Queue

This paper deals with the single-server queue with batch arrivals. We show that under suitable conditions the waiting-time distribution of an individual customer has an asymptotically exponential expansion. Computationally useful characterizations of the amplitude factor and the decay parameter are given for the practically important case in which the interarrival time and the service time have phase-type distributions.

scholarly journals Geo/Geo/1/N Queue with In-Immune and Immune Service Killing Discipline

2012 ◽  
Vol 23 (1) ◽  
pp. 129-148
Author(s):  
Madhu Jain Madhu Jain
Keyword(s):  
Performance Measures ◽  
Generating Functions ◽  
Relaxation Method ◽  
Single Server ◽  
Finite Capacity ◽  
Single Server Queue ◽  
Stationary Probability Distribution ◽  
Negative Customers ◽  
Server Queue ◽  
Successive Over Relaxation

The present investigation studies a discrete time single server queue with both positive and negative arrival streams in accordance with removal of the customer from the end (RCE)-in immune and immune service killing policy. This study is a generalization of the queue with negative customers, wherein only positive customers need a service and negative customers arriving to the system can kill the already present positive customers from any where in the queue, otherwise get lost. The concept of both in-immune and immune service killing are taken into consideration. According to the in-immune killing policy, the negative customer is allowed to kill the most recent positive customer inspite of whether it is in service or not, while the immune service killing discipline suggests that the customer currently being served is immune from killing by the negative arrival. We analyze a queue with geometric arrivals of both positive and negative customers for a finite capacity system. The stationary probability distribution and other performance measures are derived in terms of the generating functions. The results so obtained are validated by the numerical method based on successive over relaxation method (SOR). We have also employed the neurro fuzzy approach for exhibiting the approximate results for various performance measures.

A finite capacity single-server queue with customer loss

1986 ◽  
Vol 2 (1) ◽  
pp. 97-121 ◽  
Author(s):  
C. Knessl ◽  
B. J. Matkowsky ◽  
Z. Schuss ◽  
C. Tier
Keyword(s):  
Single Server ◽  
Finite Capacity ◽  
Single Server Queue ◽  
Server Queue

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

2016 ◽  
Vol 34 (2) ◽  
Author(s):  
A.N. Dudin ◽  
A.V. Kazimirsky ◽  
V.I. Klimenok ◽  
L. Breuer ◽  
U. Krieger
Keyword(s):  
Random Environment ◽  
Queueing Systems ◽  
Arrival Process ◽  
Single Server ◽  
Service Time Distribution ◽  
Finite Buffer ◽  
Phase Type ◽  
Server Queue ◽  
Finite State ◽  
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.

Exponential expansion for the tail of the waiting-time probability in the single-server queue with batch arrivals

1988 ◽  
Vol 20 (04) ◽  
pp. 880-895 ◽  
Author(s):  
J. C. W. Van Ommeren
Keyword(s):  
Waiting Time ◽  
Interarrival Time ◽  
Single Server ◽  
Waiting Time Distribution ◽  
Single Server Queue ◽  
Batch Arrivals ◽  
Exponential Expansion ◽  
Phase Type ◽  
Phase Type Distributions ◽  
Server Queue

This paper deals with the single-server queue with batch arrivals. We show that under suitable conditions the waiting-time distribution of an individual customer has an asymptotically exponential expansion. Computationally useful characterizations of the amplitude factor and the decay parameter are given for the practically important case in which the interarrival time and the service time have phase-type distributions.

Optimal Server Allocation to Parallel Queues with Finite-Capacity Buffers

1996 ◽  
Vol 10 (2) ◽  
pp. 279-285 ◽  
Author(s):  
K. M. Wasserman ◽  
Nicholas Bambos
Keyword(s):  
Arbitrary Distribution ◽  
Single Server ◽  
Finite Capacity ◽  
Dynamic Allocation ◽  
Allocation Policy ◽  
Parallel Queues ◽  
Server Allocation ◽  
Arrival Processes ◽  
Service Times ◽  
Number Of Customers

In this paper, we study the problem of dynamic allocation of a single server to parallel queues with finite-capacity buffers. The arrival processes are mutually independent, equal rate Poisson processes, and the service times are independent and identically distributed random variables with an arbitrary distribution. We are interested in characterizing the allocation policy that stochastically minimizes the number of customers lost due to buffer overflows. Using a coupling argument, we establish the optimality of the Fewest-Empty-Spaces policy, which allocates the server to the queue with the fewest empty buffer spaces, within the class of nonpreemptive and nonidling policies. The result extends to the class of preemptive policies, if the service times are exponentially distributed. We also briefly discuss the allocation problem under more general statistical assumptions on the arrival processes.

Two Extremal Autocorrelated Arrival Processes

1997 ◽  
Vol 11 (4) ◽  
pp. 441-450 ◽  
Author(s):  
Hiroshi Toyoizumi ◽  
J. George Shanthikumar ◽  
Ronald W. Wolff
Keyword(s):  
Waiting Time ◽  
Queueing Systems ◽  
Covariance Structure ◽  
Single Server ◽  
Convex Order ◽  
Increasing Convex Order ◽  
Server Queue ◽  
Arrival Processes ◽  
Extremal Processes ◽  
First In First Out

Extremal arrival processes, in the sense of increasing convex order of waiting time of queueing systems, are investigated. Two types of extremal processes are proposed: one in the class of processes that have identical marginal distributions and the other in the class of bounded stochastic processes that have the same mean and covariance structure. The worst performance with regard to waiting time in the sense of increasing convex order is guaranteed when these extremal processes are fed into a first in-first out single-server queue.

scholarly journals ANFIS and Cost Optimization for Markovian Queue with Operational Vacation

2021 ◽  
Vol 6 (3) ◽  
pp. 894-910
Author(s):  
Sonali Thakur ◽  
Anamika Jain ◽  
Madhu Jain
Keyword(s):  
Fuzzy Inference ◽  
Cost Optimization ◽  
Single Server ◽  
Finite Capacity ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Markovian Queue ◽  
Stationary Queue Length ◽  
System States ◽  
Set Up

In this paper, we investigate the M/M/1/N single server finite capacity Markovian queueing model with operational vacation and impatient behavior of the customers. To recover the server broken down during a busy period, M-threshold recovery policy along with set-up is used. Using the inflow and outflow transition rates, the state probabilities equations for different system states are constructed. For computing the stationary queue length, matrix-geometric analytic is performed. The sensitivity analysis is carried for the validation of the system performance measures. To examine the scope of the adaptive neuro-fuzzy inference system (ANFIS), computational results are presented using matric-geometric and ANFIS approaches.

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