Abstract: Modeling of a manufacturing system enables one to
identify the effects of key design parameters on the system performance and as a result to make correct decision. This paper
proposes a manufacturing system modeling approach using a spreadsheet model based on queuing network theory, in which a
static capacity planning model and stochastic queuing model are integrated. The model was used to improve the existing system utilization in relation to product design. The model incorporates few
parameters such as utilization, cycle time, throughput, and batch size.
The study also showed that the validity of developed model is good enough to apply and the maximum value of relative error is 10%, far
below the limit value 32%. Therefore, the model developed in this
study is a valuable alternative model in evaluating a manufacturing system
Abstract: In this paper, we use an M/G/C/C state dependent
queuing model within a complex network topology to determine the
different performance measures for pedestrian traffic flow. The
occupants in this network topology need to go through some source
corridors, from which they can choose their suitable exiting
corridors. The performance measures were calculated using arrival
rates that maximize the throughputs of source corridors. In order to
increase the throughput of the network, the result indicates that the
flow direction of pedestrian through the corridors has to be restricted
and the arrival rates to the source corridor need to be controlled.
Abstract: The use of buffer thresholds, blocking and adequate
service strategies are well-known techniques for computer networks
traffic congestion control. This motivates the study of series queues
with blocking, feedback (service under Head of Line (HoL) priority
discipline) and finite capacity buffers with thresholds. In this paper,
the external traffic is modelled using the Poisson process and the
service times have been modelled using the exponential distribution.
We consider a three-station network with two finite buffers, for
which a set of thresholds (tm1 and tm2) is defined. This computer
network behaves as follows. A task, which finishes its service at
station B, gets sent back to station A for re-processing with
probability o. When the number of tasks in the second buffer exceeds
a threshold tm2 and the number of task in the first buffer is less than
tm1, the fed back task is served under HoL priority discipline. In
opposite case, for fed backed tasks, “no two priority services in
succession" procedure (preventing a possible overflow in the first
buffer) is applied. Using an open Markovian queuing schema with
blocking, priority feedback service and thresholds, a closed form
cost-effective analytical solution is obtained. The model of servers
linked in series is very accurate. It is derived directly from a twodimensional
state graph and a set of steady-state equations, followed
by calculations of main measures of effectiveness. Consequently,
efficient expressions of the low computational cost are determined.
Based on numerical experiments and collected results we conclude
that the proposed model with blocking, feedback and thresholds can
provide accurate performance estimates of linked in series networks.
Abstract: In Grid computing, a data transfer protocol called
GridFTP has been widely used for efficiently transferring a large volume
of data. Currently, two versions of GridFTP protocols, GridFTP
version 1 (GridFTP v1) and GridFTP version 2 (GridFTP v2), have
been proposed in the GGF. GridFTP v2 supports several advanced
features such as data streaming, dynamic resource allocation, and
checksum transfer, by defining a transfer mode called X-block mode.
However, in the literature, effectiveness of GridFTP v2 has not been
fully investigated. In this paper, we therefore quantitatively evaluate
performance of GridFTP v1 and GridFTP v2 using mathematical
analysis and simulation experiments. We reveal the performance
limitation of GridFTP v1, and quantitatively show effectiveness of
GridFTP v2. Through several numerical examples, we show that by
utilizing the data streaming feature, the average file transfer time of
GridFTP v2 is significantly smaller than that of GridFTP v1.
Abstract: Network management techniques have long been of
interest to the networking research community. The queue size plays
a critical role for the network performance. The adequate size of the
queue maintains Quality of Service (QoS) requirements within
limited network capacity for as many users as possible. The
appropriate estimation of the queuing model parameters is crucial for
both initial size estimation and during the process of resource
allocation. The accurate resource allocation model for the
management system increases the network utilization. The present
paper demonstrates the results of empirical observation of memory
allocation for packet-based services.
Abstract: Most of the real queuing systems include special properties and constraints, which can not be analyzed directly by using the results of solved classical queuing models. Lack of Markov chains features, unexponential patterns and service constraints, are the mentioned conditions. This paper represents an applied general algorithm for analysis and optimizing the queuing systems. The algorithm stages are described through a real case study. It is consisted of an almost completed non-Markov system with limited number of customers and capacities as well as lots of common exception of real queuing networks. Simulation is used for optimizing this system. So introduced stages over the following article include primary modeling, determining queuing system kinds, index defining, statistical analysis and goodness of fit test, validation of model and optimizing methods of system with simulation.
Abstract: Probabilistic measures of uncertainty have been
obtained as functions of time and birth and death rates in a queuing
process. The variation of different entropy measures has been studied
in steady and non-steady processes of queuing theory.
Abstract: The transient analysis of a queuing system with fixed-size batch Poisson arrivals and a single server with exponential service times is presented. The focus of the paper is on the use of the functions that arise in the analysis of the transient behaviour of the queuing system. These functions are shown to be a generalization of the modified Bessel functions of the first kind, with the batch size B as the generalizing parameter. Results for the case of single-packet arrivals are obtained first. The similarities between the two families of functions are then used to obtain results for the general case of batch arrival queue with a batch size larger than one.
Abstract: This paper introduces a technique for simulating a
single-server exponential queuing system. The technique called the
Q-Simulator is a computer program which can simulate the effect of
traffic intensity on all system average quantities given the arrival
and/or service rates. The Q-Simulator has three phases namely: the
formula based method, the uncontrolled simulation, and the
controlled simulation. The Q-Simulator generates graphs (crystal
solutions) for all results of the simulation or calculation and can be
used to estimate desirable average quantities such as waiting times,
queue lengths, etc.
Abstract: The paper considers a single-server queue with fixedsize
batch Poisson arrivals and exponential service times, a model
that is useful for a buffer that accepts messages arriving as fixed size
batches of packets and releases them one packet at time. Transient
performance measures for queues have long been recognized as
being complementary to the steady-state analysis. The focus of the
paper is on the use of the functions that arise in the analysis of the
transient behaviour of the queuing system. The paper exploits
practical modelling to obtain a solution to the integral equation
encountered in the analysis. Results obtained indicate that under
heavy load conditions, there is significant disparity in the statistics
between the transient and steady state values.
Abstract: A new conceptual architecture for low-level neural
pattern recognition is presented. The key ideas are that the brain
implements support vector machines and that support vectors are
represented as memory patterns in competitive queuing memories. A
binary classifier is built from two competitive queuing memories
holding positive and negative valence training examples respectively.
The support vector machine classification function is calculated in
synchronized evaluation cycles. The kernel is computed by bisymmetric
feed-forward networks feed by sensory input and by
competitive queuing memories traversing the complete sequence of
support vectors. Temporary summation generates the output
classification. It is speculated that perception apparatus in the brain
reuses structures that have evolved for enabling fluent execution of
prepared action sequences so that pattern recognition is built on
internalized motor programmes.
Abstract: Decrease in hardware costs and advances in computer
networking technologies have led to increased interest in the use of
large-scale parallel and distributed computing systems. One of the
biggest issues in such systems is the development of effective
techniques/algorithms for the distribution of the processes/load of a
parallel program on multiple hosts to achieve goal(s) such as
minimizing execution time, minimizing communication delays,
maximizing resource utilization and maximizing throughput.
Substantive research using queuing analysis and assuming job
arrivals following a Poisson pattern, have shown that in a multi-host
system the probability of one of the hosts being idle while other host
has multiple jobs queued up can be very high. Such imbalances in
system load suggest that performance can be improved by either
transferring jobs from the currently heavily loaded hosts to the lightly
loaded ones or distributing load evenly/fairly among the hosts .The
algorithms known as load balancing algorithms, helps to achieve the
above said goal(s). These algorithms come into two basic categories -
static and dynamic. Whereas static load balancing algorithms (SLB)
take decisions regarding assignment of tasks to processors based on
the average estimated values of process execution times and
communication delays at compile time, Dynamic load balancing
algorithms (DLB) are adaptive to changing situations and take
decisions at run time.
The objective of this paper work is to identify qualitative
parameters for the comparison of above said algorithms. In future this
work can be extended to develop an experimental environment to
study these Load balancing algorithms based on comparative
parameters quantitatively.
Abstract: In this research, we propose a weighted class based
queuing (WCBQ) mechanism to provide class differentiation and to
reduce the load for the IMS (IP Multimedia Subsystem) presence
server (PS). The tasks of admission controller for the PS are
demonstrated. Analysis and simulation models are developed to
quantify the performance of WCBQ scheme. An optimized dropping
time frame has been developed based on which some of the preexisting
messages are dropped from the PS-buffer. Cost functions are
developed and simulation comparison has been performed with FCFS
(First Come First Served) scheme. The results show that the PS
benefits significantly from the proposed queuing and dropping
algorithm (WCBQ) during heavy traffic.
Abstract: The paper shows that in the analysis of a queuing system with fixed-size batch arrivals, there emerges a set of polynomials which are a generalization of Chebyshev polynomials of the second kind. The paper uses these polynomials in assessing the transient behaviour of the overflow (equivalently call blocking) probability in the system. A key figure to note is the proportion of the overflow (or blocking) probability resident in the transient component, which is shown in the results to be more significant at the beginning of the transient and naturally decays to zero in the limit of large t. The results also show that the significance of transients is more pronounced in cases of lighter loads, but lasts longer for heavier loads.
Abstract: In this work, we study the impact of dynamically changing link slowdowns on the stability properties of packetswitched networks under the Adversarial Queueing Theory framework. Especially, we consider the Adversarial, Quasi-Static Slowdown Queueing Theory model, where each link slowdown may take on values in the two-valued set of integers {1, D} with D > 1 which remain fixed for a long time, under a (w, p)-adversary. In this framework, we present an innovative systematic construction for the estimation of adversarial injection rate lower bounds, which, if exceeded, cause instability in networks that use the LIS (Longest-in- System) protocol for contention-resolution. In addition, we show that a network that uses the LIS protocol for contention-resolution may result in dropping its instability bound at injection rates p > 0 when the network size and the high slowdown D take large values. This is the best ever known instability lower bound for LIS networks.
Abstract: In this paper, a mathematical model is proposed to
estimate the dropping probabilities of cellular wireless networks by
queuing handoff instead of reserving guard channels. Usually, prioritized
handling of handoff calls is done with the help of guard channel
reservation. To evaluate the proposed model, gamma inter-arrival and
general service time distributions have been considered. Prevention of
some of the attempted calls from reaching to the switching center due
to electromagnetic propagation failure or whimsical user behaviour
(missed call, prepaid balance etc.), make the inter-arrival time of
the input traffic to follow gamma distribution. The performance is
evaluated and compared with that of guard channel scheme.
Abstract: Mobile Ad hoc networks (MANETs) are collections
of wireless mobile nodes dynamically reconfiguring and collectively
forming a temporary network. These types of networks assume
existence of no fixed infrastructure and are often useful in battle-field
tactical operations or emergency search-and-rescue type of
operations where fixed infrastructure is neither feasible nor practical.
They also find use in ad hoc conferences, campus networks and
commercial recreational applications carrying multimedia traffic. All
of the above applications of MANETs require guaranteed levels of
performance as experienced by the end-user. This paper focuses on
key challenges in provisioning predetermined levels of such Quality
of Service (QoS). It also identifies functional areas where QoS
models are currently defined and used. Evolving functional areas
where performance and QoS provisioning may be applied are also
identified and some suggestions are provided for further research in
this area. Although each of the above functional areas have been
discussed separately in recent research studies, since these QoS
functional areas are highly correlated and interdependent, a
comprehensive and comparative analysis of these areas and their
interrelationships is desired. In this paper we have attempted to
provide such an overview.
Abstract: Main goal of preventive healthcare problems are at
decreasing the likelihood and severity of potentially life-threatening
illnesses by protection and early detection. The levels of
establishment and staffing costs along with summation of the travel
and waiting time that clients spent are considered as objectives
functions of the proposed nonlinear integer programming model. In
this paper, we have proposed a bi-objective mathematical model for
designing a network of preventive healthcare facilities so as to
minimize aforementioned objectives, simultaneously. Moreover, each
facility acts as M/M/1 queuing system. The number of facilities to be
established, the location of each facility, and the level of technology
for each facility to be chosen are provided as the main determinants
of a healthcare facility network. Finally, to demonstrate performance
of the proposed model, four multi-objective decision making
techniques are presented to solve the model.
Abstract: How to effectively allocate system resource to process
the Client request by Gateway servers is a challenging problem. In
this paper, we propose an improved scheme for autonomous
performance of Gateway servers under highly dynamic traffic loads.
We devise a methodology to calculate Queue Length and Waiting
Time utilizing Gateway Server information to reduce response time
variance in presence of bursty traffic. The most widespread
contemplation is performance, because Gateway Servers must offer
cost-effective and high-availability services in the elongated period,
thus they have to be scaled to meet the expected load. Performance
measurements can be the base for performance modeling and
prediction. With the help of performance models, the performance
metrics (like buffer estimation, waiting time) can be determined at
the development process. This paper describes the possible queue
models those can be applied in the estimation of queue length to
estimate the final value of the memory size. Both simulation and
experimental studies using synthesized workloads and analysis of
real-world Gateway Servers demonstrate the effectiveness of the
proposed system.
Abstract: In this paper, we consider the effect of the initial
sample size on the performance of a sequential approach that used
in selecting a good enough simulated system, when the number
of alternatives is very large. We implement a sequential approach
on M=M=1 queuing system under some parameter settings, with a
different choice of the initial sample sizes to explore the impacts on
the performance of this approach. The results show that the choice
of the initial sample size does affect the performance of our selection
approach.