Analysis of iFogSim and EmuFog: Fog Computing Simulating Tools

This paper provides a comprehensive overview of fog computing and the simulating tools used within this domain. It begins with an introduction to fog computing, highlighting its significance in smart environments and its role in bringing cloud computing closer to end-users, thereby improving access speed and efficiency compared to traditional cloud models. The core of the paper focuses on two primary simulation tools: iFogSim and EmuFog. iFogSim, an open-source toolkit, is described as a valuable resource for simulating fog, edge, and IoT networks, integrating resource management techniques. The paper outlines the installation process, the various components, and the GUI implementation of iFogSim. In contrast, EmuFog is presented as a tool designed for large-scale network emulation, allowing developers to study fog computing scenarios effectively. The paper details the four stages of EmuFog's workflow: topology generation, transformation, enhancement, and deployment, emphasizing its ability to simulate various fog computing environments and deploy applications using Docker containers. The paper concludes by highlighting the importance of these simulation tools in advancing the field of fog computing.

Fog Computing
Simulating Tools for Fog Computing
Abstract— The paper is aiming to describe the various simulating tools of Fog Computing. In the paper it is briefly described about Fog
computing. The paper describes about the simulating tools of Fog Computing. The two different simulating tools discussed in the paper
are iFogSim and EmuFog. The ways that are used to use the tools are described and along with brief explanation. The paper concludes
the uses of the simulating tools in the field of Fog Computing.
Keywords-Fog Comouting; iFogSim; EmuFog (key words)
I. INTRODUCTION
The aim of the paper is to describe the various simulating
tools of Fog Computing. In the paper it is briefly described
about Fog computing. After the description of Fog computing
the paper discussed the simulating tools that supports Fog
Computing. The simulating tools include iFogSim and
EmuFog. A detailed description is given on the two different
simulating tools [1]. It is also mentioned that the two tools
beside of supporting the Gog Computing also supports the
Cloud computing.
II. FOG COMPUTING
Fog computing is such a platform that is gaining enough
prominence in the smart environments that are based on
network. Fog computing was launched by Cisco which aims to
bring cloud computing close to that of the control region and
the management region in case of end users. Fog computing
help all its users with access to the services. This also makes
the access speed faster when it is compared to cloud
computing in case of delivery purpose [2]. Fog computing is
connected with fog networking and with fogging. In case of
fog computing a computer environment is created that is
decentralized in nature. In case of the approach the storage,
objects, data analytics, services and applications are deployed
which are in the middle of the local systems and the remote
data center [3]. This is the way by which the original resources
of the users get closer to them and they do not need to access
all of them through the internet.
III. FOG
Fog computing is defined as the layer which is in between the
cloud and end users. It also addresses all the issues in case of
the bandwidth, jitter, delay and latency [4]. All this mentioned
issues can be easily avoided with the help of fog computing.
Fog computing are used to improve the network environment
performance. The range of Fog Computing is low, but within
that range it have good access to all its resources. The use of
Fog Computing benefits the below mentioned parameters.
 Latency
 Capacity
 Bandwidth
 Responsiveness
 Security
 Speed
 Robustness
 Fault tolerance
 Data integration
 Energy
IV. SYSTEMS TOOLS FOR USING FOG COMPUTING
A. iFogSim
This is referred to a toolkit that is open source used in case of
fog computing. Beside of Fog Computing this is also used for
Edge Computing and IoT. iFogSim simulates network in case
of Fog Computing [5]. This also integrates the technique of
resource management which is even modified according to the
area of research.
iFogSim is associated with CloudSim which a library that is
used widely in case to simulate the environments that are
based on cloud computing [6]. The layers of CloudSim
handles all the events which are in between all the components
that are of fog computing. In this case it uses iFogSim [7].
There are various classes of iFogSim which are used for
simulating the network of fog:
 Fog device
 Sensor
 Actuator
 Tuple
 Application
 Monitoring edge
 Service of Resource management
Installation of iFogSim is such an easy process. The library of
iFogSim can be downloaded from a specific URL. JDK is
required for customizing the toolkit and to work in the toolkit.
As the compression toolkit is downloaded in Zip format
extraction of the zip is done which creates a dedicated folder.
Any IDE can use the can execute the library including Eclipse,
BlueJ, Jdeveloper and many more.
Networks can be simulated with the help of iFogSim. Various
Java code package are used to implement Fog Computing. In
case to work with iFogSim in GUI there is a dedicate file that
is known as the FogGUI.java. This is the file which is
executed directly to IDE. Beside to this there are several fog
components and cloud components which are imported for
simulating the area of work. The topology can also be
implemented with the help of the Fog Topology Creator. After

the execution the output is displayed in the Eclipse IDE. There
are various scenarios in iFogSim in case of the multiple
applications which can also be simulated. In this case it
includes SDN along with the integration with fog computing.
There are modifiable libraries which can also be improved
with these of the algorithms. These are the algorithms which
are programmed with the help of the iFogSim libraries. In this
way the performance of the new algorithm that will be
analyzed based on the network of fog by the use of iFogSim.
B. EmuFog
There are various objectives of design that are implemented by
EmuFog [8]. Large topology networks are emulated by
EmyFog which give allowance to the developer for studying
the scenarios of Fog Computing that are in large scale.
EmuFog also makes easier for the developers in case to make
package of the applications and also to run in the environment
that is emulated. All the EmuFog components are replaceable
and also extensible with the help of the components that are
custom build.
The workflow of EmuFog at the time of performing of their
emulations of the Fog Computing are divided in four different
ways:
 Topology Generation- BRITE is one of the topology
generator which creates a network topology. This is
the network topology which is loaded fro, file that
also allows the datasets to include with the topology
of the real world.
 Topology Transformation- In case of EmuFog the
network can be represented like a graph that is
indirected and are connected with various links along
with latency and certain throughput. The devices of
networks here are grouped with various autonomous
systems. Thus in this way the topology can be
translated into a specific model of topology of
EmuFog [9].
 Topology Enhancement- The topology network
along with the Fog nodes are enhanced. In this way
there are two different steps that are performed in
which firstly the edge in case of topology of network
is determined and secondly in the topology of the
network the Fog nodes are inserted which are done in
accordance to the policy of placement.
 Deployment and Execution- In the environment of
emulation a network topology which is enhanced is
deployed. The Fog nodes are also placed in the
network which is emulated and in the application
components that is provided by the containers of
Docker which is also deployed on the basis of Fog
nodes.
This are the following ways using of which the developers of
application are capable to evaluate the applications of Fog
computing in various environments of Fog. All the different
steps of workflow in case of EmuFog can be implemented
with the accordance of the need of the users. Though various
implementation sets are provided by the EmuFog which serves
huge set of emulation scenarios of Fog Computing. A
component to generate topology is also provided by the
EmuFog for generating the topologies of their Internet scale.
This is the topology that is based the network of BRITE [10].
An adapter is also there which translate the topologies of
BRITE network in the topologies of real world taken from
CAIDA and ITDK, which is the model of network topology of
EmuFog. This are the components which are simple.
In case of EmuFog a placement policy which is latency based
is implemented to keep a bounded latency that is between the
clients who are connecting the edge of the network and the
Fog node that is closest.
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