Comparison of Cloud Simulators for effective modeling of Cloud
applications
Shobhna Dogra Department of Computer Science, Himachal Pradesh University, Shimla, Himachal Pradesh, India
A.J Singh Department of Computer Science, Himachal Pradesh University, Shimla, Himachal Pradesh, India
ABSTRACT
Cloud computing is a style of computing through which massively scalable or flexible IT-related ability can be provided in
the form of services. With the help of internet technologies, infrastructure, platform, application, or storage space facilities
can be made available in these services in which we can use the service according to our needs and pay for those services
which we use. As cloud computing is a huge collection of resources, which involves a large amount of money and cost, so
software is required where we can instead of creating the cloud we can simulate the exact atmosphere to monitor the results.
There are various cloud simulation tools available over the internet. In this paper we have selected the three popular cloud
simulators a) CloudSim b) CloudAnalyst c) CloudReport to present their abilities. As most of the cloud simulators have
almost similar architectures and functions, the difference is based on their capability and extensibility. These cloud
simulators are software-based simulation tools and are analyzed based on different parameters to find the capabilities of each
cloud simulator. The experimental comparison of these tools is done to find out the best tool for cloud simulation.
Keywords: Cloud Computing, Simulation tools, CloudSim, CloudAnalyst, CloudReport, Data centers,
Virtual machines, Resource utilization.
1. INTRODUCTION
Cloud computing is a pattern around the globe and all the individuals are moving towards it leaving customary
figuring behind. This is because of the guarantee of cost decrease, more prominent adaptability, flexibility,
versatility, on request get to, asset use, insignificant foundation the executives, and area freedom[1]. Cloud
computing is the quickest rising innovation that offers an inventive plan of action for associations to receive IT
without an advanced venture. Industries, for example, Amazon, Google, Microsoft, HP, and IBM have
vigorously contributed to it. Cloud computing alludes to both the applications conveyed as administrations over
the Internet and the equipment and frameworks programming in the datacentres that offer those types of
assistance[2]. Simulation is a science and technique for making a model of a process or a real system and
designed to test strategies and figure out the behavior of a system under certain circumstances using various
strategies[3]. Performing experiments in a real environment are expensive, time costly, and not repeatable, also
it is hard to analyze the performance and security issues on actual cloud environments. That's why modeling and
simulation technology is becoming popular in the field cloud industry[4]. A cloud simulation platform discovers
the required resources automatically and built a simulation system on-demand based on service-oriented
composition and scheduling[5]. It is the process of creating a prototype of an actual real-world model over small
infrastructure to monitor the results. Simulation is required as cloud computing is a huge collection of resources
and it requires a large amount of money and infrastructure so, we simulate the cloud for a particular application
to check its feasibility. It is a tool that will help us in giving a repeatable and controlled environment for
running, testing, and discovering limitations in algorithms and services. We are going to run the application in a
controlled environment, so it provides us the possibilities of evaluating the supposition which we have made
regarding the applications. Mainly two types of cloud computing simulators exist, the one which are based on
the software and other one are based on both software as well as hardware[6].
In this paper, a discussion on the simulation tools that are used to test the applications is done. A comparison of
three popular simulation tools that are i)CloudSim ii)CloudAnalyst iii)CloudReport based on the different
criteria's is done. This paper is organized as follows: Section II gives the details about related work; Section III
contains the experimental results obtained by running these simulation tools and Section IV provides the
conclusion.
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2. RELATED WORK
A lot of research work has been done on cloud simulators which focus on finding their main features,
advantages, and disadvantages. CloudSim tool was developed in the CLOUDS Laboratory at the Computer
Science and Engineering Department of the University Of Melbourne, Australia[7]. Due to insufficient trace
logs available for analysis, workload modeling becomes difficult, so a web application model is proposed to
support analysis and simulation of resource utilization in a cloud environment which can easily be reproduced
by cloud providers to support different research domain[8]. CloudSim is a toolkit or library of java classes for
simulation. A new simulation tool FTCloudSim is proposed by extending the basic functionality of CloudSim
which models and simulates the cloud service reliability enhancement mechanisms to overcome a shortage of
tools that enable researchers to calculate their new proposed cloud service reliability enhancement[9]. A new
service broker strategy in CloudAnalyst is proposed by the author that extends the service proximity-based
routing policy that selects the data center from the data centers within the same region is done cost-
effectively[10]. Various load balancing techniques are analyzed using tool CloudAnalyst and it is analyzed that
the load balancing technique does not play any role in the processing cost[11]. An efficient cloud-based
simulation framework is proposed called WeaveSim which extends CloudSim with AOP(aspect-oriented
programming) concepts that reduce the complexity of modelling and simulating the custom and dynamic
behavior of cloud-based applications. It also reduces the complexity of implementing cross-cutting concerns on
cloud-based software systems that increases the reusability, scalability, and maintainability of the cloud-based
software systems[12].
3. CLOUD SIMULATION TOOLS
Simulation tools are used to evaluate the performance of cloud applications before deploying them in a real
environment[13]. It provides us a test environment in which applications are run to te check whether the
applications are running properly or not. The simulation tools: CloudSim, CloudAnalyst, CloudReport are open
source tools and can be downloaded from the website “The Cloud Computing and Distributed Systems
(CLOUDS) Laboratory, the University of Melbourne”[14] free of cost.
1.CloudSim: CloudSim tool was developed in the CLOUDS Laboratory at the Computer Science and
Engineering Department of the University Of Melbourne, Australia. Cloudsim is a java library, in which we can
write a java program to frame the desired structure and get the desired results for analyzing cloud applications.
We can simulate infrastructure including data centers on a large scale easily on a single physical node.
CloudSim is a simple simulator and is suitable for simulation of batch tasks, and is not able to support stream
tasks (i.e. continuous computation)[15]. CloudSim is easy to use and easily extensible simulation toolkit and
application which provides easy modeling, simulation, and experimentation on existing or developing cloud
system, infrastructures and application environments for single and internetworked clouds. The existing
distributed system simulators were not pertinent for the cloud computing environment due to evaluating the
performance of cloud provisioning policies, services, application workload, models, and resources under the
varying system, user configurations and requirements[16].
CloudSim experiment:
In this experiment, data centers and virtual machines are created which running on one host. The Number of
data centres=3, the number of VM =15. Eighty cloudlets are submitted to these virtual machines as shown in
figure 1.
Simulation is completed in 5 seconds. After the completion of the simulation, the results are represented in the
console window as shown in figure 2. This console contains cloudlet ID, data center ID, Virtual machine ID,
starting time, and finishing time of each cloudlet.
2. CloudAnalyst: CloudAnalyst is designed by Wickremasinghe et al.[7] to avail understand how a sizable
Internet application comports in the context of a cloud environment. Cloud analyst is a CloudSim based tool
which helps in modeling and analysis of large scale cloud computing environments. The cloud analyst tool was
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designed to observe how large scale internet applications behave in a cloud environment[17]. Cloud analyst
enables the user to repeatedly perform simulation experiments and to perform the same with slight changes in
parameters very easily and quickly and generates efficient output as per the changes in parameters. The results
of the simulation are obtained in the form of graphical output that makes it easy to analyse the results more
easily and problems related to performance and accuracy of simulation logic can be identified quickly[18].
Figure 1: representing cloudlet and data center ID.
Figure 2: total time taken to complete the simulation
CloudAnalyst experiment::
In this analysis, the cloud environment contains three user bases that are topographically spread in three
regions i.e. regions 2,3 and 1. The number of Data centre=3 and Service broker policy used is the Optimise
Response Time(ORT)[19] policy which will search for the data center which will process requests fast.
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Simulation time=15 minutes, number of users= 3, number of requests generated per user =60 per hour for each
user, number of virtual machines=5 each are shown in this figure 3.
The data center configuration provides the information about the data center, the region in which these data
center lies and detailed information about physical hardware of each data center for each data center i.e. the
number of processors=4, amount of storage=100000000mb, network bandwidth=1000000 as shown in figure 4.
Figure 3: main configuration window
Figure 4: data center configuration window.
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After the simulation configuration is completed, CloudAnalyst shows the region with response time
results as shown in figure 5.
Figure 5: CloudAnalyst framework
After running simulation the results presented are in the form of charts and tables and also provide the feature
of displaying detailed results through which we can export the results in the form of a pdf file. Detail about total
virtual machine cost and total data transfer cost is also provided as shown in figure 6.
3. CloudReport: CloudReports is a graphical tool that simulates distributed cloud computing environments. It
is a derivative of CloudSim with a graphical user interface that makes up a user-friendly environment and
provides more customizability and repeatability based on different parameters. Graphical User Interface enables
users to carry out their tasks easily. CloudReports is a useful tool in the field of energy-aware cloud computing
environments. Users can easily document their results after the simulation process and it also provides the
functionality of producing and amending policies via the Application Package Interface(API).
After the completion of the simulation, CloudReport generates the results in the form of charts and tables
which contains information about the VM allocation, energy consumption, execution time,resource usage cost,
and all the user-defined characteristics[20].
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Figure 6: Overall response time summary and total VM and data transfer cost.
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CloudReport Experiment:
In this analysis, it is assumed that in a simulated environment as shown in figure 7 here are three data
centers with seven hosts(physical machines), processing unit=28 (4 processing unit each), processing
capacity=67,200MIPS (microinstructions per second), storage capacity= 37TB, Total amount of
RAM= 280GB
Configuration of each data center can be done according to the user requirements. each data center
chooses an allocation policy according to the user requirements. For data center 1 the Allocation
policy= Single threshold, scheduling interval=30, monitoring interval=180, number of host=3, number
of processing units=12, processing capacity=28,800MIPS, storage capacity=13TB, Total amount of
RAM=120GB as shown in figure 8.
Also, the configuration of the user base or customer is done. In this experiment, three user base or
customer are created with two virtual machines each. 150 cloudlets are sent per minute as shown in
figure 9.
Figure 7: CloudReport framework
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Figure 8: data center configuration
Figure 9: customer configuration
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After the end of the configuration of the provider (data center) and customer (user base) simulation is
executed and the results obtained are in the form of an HTML report. This report contains charts that
represent the resource utilized, the power consumed, and the overall resource utilized by each data
center as shown in figure 10.
Figure 10: overall resource utilization of data center
Also, the report of overall resource utilization and execution time of cloudlets for customer 1 is shown
in figure 11.
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Figure 11: overall resource utilization and execution time of the selected customer
After running these simulators now we are going to compare them based on different
parameters[1][21][22]. Various parameters considered are explained as follows:
1. Underlying Platform: It refers to the existing framework as some cloud simulators are built upon
some existing simulation framework, i.e. they are extended form of an existing one.
2. IaaS: IaaS(Infrastructure as a service) offers virtual machines and other resources[23].
3. PaaS: Platform as a service provides an operating system, programming language execution
environment, database, and web server as a computing platform[23].
4. SaaS: SaaS(Software as a service) cloud providers provide the right to the clients to use the
application software and databases[23].
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5. Programming Language: It refers to the language required for working with a specific simulator.
6. Cost Modelling: The user wants to work on cost modeling as the cloud is pay per use model so he
must make the right choice of the simulator.
7. Simulation Speed: It is the time taken by the simulator to complete or run the simulation.
8. Migration Policy: it refers to where and when to migrate a VM.
9. Physical Modelling: refer to the modeling of physical layer entities such as cache and allocation
policies for memory.
10. Application Model: it refers to the models that are supported by the framework for different
applications.
11. Load balancing: It refers to the mechanism that decides which node will be sent to the virtual
machine and which node will be put on hold[11].
12. Communication modeling: It refers to the communication that takes place in the simulator.
Table 1 2 3 shows the comparison based on different criteria which are shown as follow :
Table (1): A comparison based on the cloud service related environment.
Simulator
Requirements
CloudSim CloudAnalyst CloudReport
IaaS Yes Yes Yes
PaaS No No No
SaaS No No Yes
Migration policy Yes No No
Table (2): A comparison based on could components modeling requirements.
Simulator
Requirements
CloudSim CloudAnalyst CloudReport
Cost modeling Yes Yes Yes
Communication modeling Limited Limited No
Physical modeling No No Yes
Application models Computation and
data transfer
Computation and data
transfer
Computation and data
transfer
Table (3): A comparison based on simulation related requirements.
Simulator
Requirements
CloudSim CloudAnalyst CloudReport
Underlying platform SimJava CloudSim/SimJava CloudSim
Graphical interface No Yes Yes
Programming language used Java Java Java
Load balancing Yes Yes No
Power consumption Yes No Yes
Social network Yes/No Yes No
Simulation speed Mid High High
From table 1, 2, 3 it is observed that infrastructure as service is provided by each simulator and none of these
simulators provides a platform as a service and only CloudReport provides the feature of software as a service.
All the simulators are used for computation and data transfer purposes. Except for CloudSim, both the other
simulators provide GUI(graphical user interface) to the clients which makes it easy to use the simulator. The
simulation speed of all the simulators is fast and displays the results in seconds. Only CloudReport supports
physical modeling for allocating policies. CloudSim is only the simulator that supports migration policy which
helps to avoid bottlenecks, improve the availability of resources. CloudSim and CloudAnalyst provide the load
balancing which prevents any single server from getting overloaded with resources. CloudAnalyst and
CloudReport are the extensions of CloudSim that is they use CloudSim as platform and java is the programming
language that is used in all the three simulators
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4. CONCLUSION
Cloud computing is one of the fastest-growing technology in IT sectors. We use various cloud simulators for
calculating the cloud computing systems and application activities and analyzing the performance of cloud
computing environments. If we want to measure Resource utilization and implementation cost then CloudReport
is the best choice. CloudAnalyst is best when we need to calculate the social network and response time. And
for analyzing complex simulations CloudSim is the best tool out of all these three tools. No simulation tool is
the overall best tool, as each simulator has its advantages and disadvantages so we have to choose the right
simulator according to the situation and the user requirements.
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