World Journal of Engineering and Technology, 2013, 1, 23-25
http://dx.doi.org/10.4236/wjet.2013.12004 Published Online August 2013 (http://www.scirp.org/journal/wjet)
Simulation on Single Server & Distributed Environment
(It’s Comparison & Issues)
A. Jawwad Memon1, Wasi Ur Rehman2
1Department of Computer Science, Institute of Business & Technology (IBT), Karachi, Pakistan; 2Department of Computer Science,
Institute of Business & Technology (IBT), Karachi, Pakistan.
Received June 3rd, 2013; revised July 6th, 2013; accepted August 2nd, 2013
Copyright © 2013 A. Jawwad Memon, Wasi Ur Rehman. This is an open access article distributed under the Creative Commons
Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is
properly cited.
ABSTRACT
Simulation has become the evaluation method of choice for many areas of distributing computing research. Simulation
has been applied successfully for modeling small and large complex systems and understanding their behavior, espe-
cially in the area of distributed systems or parallel environment. The aim of my research is to study and qualitative
analysis of simulation on a single server & on distributed environment and finding the related issues & its comparison.
Keywords: Simulation; Simulation on Single Server Environment; Simulation on Distributed Environment; Simulation
Issues
1. Introduction
The terms “simulation” and “modeling” are sometimes
used alternatively. In reality, they are distinct, though
related, terms.
Simulation means mimicking of real life or potential
situations, usually using computers. It is the imitative
representation of the functioning of one system or proc-
ess by means of the functioning of another, such as a
computer simulation of an industrial process. With simu-
lation, one can examine a problem that is often not sub-
ject to direct experimentation.
1.1. Basic Simulation Model
Basic simulation model structure is shown in Figure 1.
Simulation is the art of using tools—physical or con-
ceptual models, or computer hardware and software, to
attempt to create the illusion of reality. The discipline has
in recent years expanded to include the modeling of sys-
tems that rely on human factors and therefore possess a
large proportion of uncertainty, such as social, economic
or commercial systems.
Simulation is the technique of using some tools—ei-
ther physical or conceptual models, or based on computer
Experiment with the actual systemExperiment with a model of the system
Physical ModelMathematical Model
Analytical ModelSimulation
System
Figure 1. Basic simulation model structure [1].

Simulation on Single Server & Distributed Environment (It’s Comparison & Issues) 24
hardware and software; try to create the virtual illusion of
real objects [2].
1.2. Simulation Purpose: When to Use
 The study of experiments: Simulation enables with
internal interactions.
 Knowledge gained from simulations very useful in
order to improve the system.
 Simulations can be used to verify analytical results,
e.g. queuing systems [3].
2. Literature Review
Applications, Models, Simulation & Design Models are
shown in Figure 2.
2.1. Simulation on Single Server Environment
Simulation on a single server environment is based on
client server architecture where its work on single pc
environment.
In the area of IT, client-server models exhibit a degree
of complexity and richness not amenable to easy ana-
lytical solutions, except for some specific algorithms
useful in limited contexts. Simulation could, therefore, be
a good strategy to analyze the client-server systems and
help in better implementation of feasible solutions [4].
2.2. Simulation on Distributed Environment
Any simulation in which the number of processors is
more than 1 involved [5].
Distributed systems typically consist of a large number
of actors that act and interact with each other in a highly
dynamic or changing environment [6].
Design and development of distributed system is
widespread in discrete-event simulation, for example: it
is use to understand network protocols [7].
Performance and functionality of complex inter com-
ponent protocol and algorithm is defined by simulation,
these functions and algorithms written in different pro-
gramming languages.
Simulation gives an opportunity to developer to cap-
ture basic functionality at the same time as they are
working on topology, bandwidth, timing and overall pro-
perties of distributed system. The code that implements a
simulation distributed system is formal speciation of the
intended functional behavior of that system, whose be-
havior is parameterized by a well-defined set of control-
lable distribution properties in addition to normal inputs
[8].
According to this observation, simulation can be used
within a specification based testing to provide developers
of distributed system with a method for selective effec-
tive test suites. This analysis give advantage of specifica-
tion is executable to program code, in concern of distrib-
uted system and the simulation code is correct specifica-
tion.
2.3. Why Use Simulation
 It makes the simulation process faster with large
number of processors.
 It simulate larger amount of data with greater memory
& resources.
 It integrates geographically distributed simulators [9].
3. Related Work
3.1. Simulation on Single Server Environment
Processing performed in single server environment is
shown on Figure 3. It clearly shows simulation on a sin-
gle server environment in which we have single processor.
3.2. Simulation on Distributed Environment
Processing performed in distributed environment is
shown in Figure 4. It clearly shows simulation on a dis-
tributed environment in which we have multiple proces-
sors.
Application
Areas
Parallel and Distributed
Simulation &
Design Models
Models
Simulation
Simulation
Model
Industrial
Processes
Environmental
Resources
Many other
applications
…
Design
Model
Discrete
event
Continuous
event
Visual-
based
Library-
based
Hibrid
(discrete and
continuous)
Systems
Figure 2. Applications, models, simulation & design models [6].

Simulation on Single Server & Distributed Environment (It’s Comparison & Issues) 25
Sequential
1 processors
Example:
Figure 3. Processing performed in single server environment.
P
arallel
n
> 1 processors
E
xample:
2
processors
Figure 4. Processing performed in distributed environment.
3.3. Comparison: Simulation in Single Server
Environment
 Simulation performed on single server.
 It has geographic limitation due to single server.
 Single processor use.
 It makes the simulation process slower because single
core processor use in simulation.
 The cost of setup is comparatively low.
 To maintain one server is easy as compared to multi-
ple servers.
3.4. Comparison: Simulation in Distributed
Environment
 Simulation performed on distributed servers.
 It integrates geographically distributed simulators.
 Multiple processor use.
 It makes the simulation process faster because single
core processor use in simulation
 The cost of is high because multiple processors used.
 It’s quite difficult job to maintain huge no. of servers
on distributed environment.
4. Conclusion
Simulation has been applied successfully for modeling
small and large complex systems. Simulation is the art to
create a physical and conceptual model which can repre-
sent a system or create the illusion of reality. Simulation
helps to make experiment for understanding the behavior
of system. Computer simulation gives opportunity to
observe a real world experience and interact with it. As
we all know that purchasing physical equipment for
every experiment is almost not possible and required a
large amount of funding.
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