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Location-based services are now extremely prevalent due to their massive usage in current and emerging technologies. The use of simulation tools has been gaining popularity in the domain of LBS systems, where researchers take advantage of simulators for evaluating the behavior and performance of new architecture design. This popularity results from the availability of various powerful and sophisticated LBS simulators that are continuously verifying the flexibility of proposed models of LBS research projects. Despite its popularity worldwide, there is still a problem for researchers to choose the best simulator according to their needs and requirements, which provide them accurate results. Furthermore, conducting research on the physical LBS environment for individuals or small educational institutes is very challenging due to the cost involved in setting up location-based services live. Therefore, for selecting an appropriate LBS simulator, it is important to have knowledge of simulators that are currently available along with their features and selection criteria considered for conducting research in a particular type of problems in the LBS system. In the current study, we have presented various simulators that provide a cost-effective way of conducting LBS research projects. This paper compares 10 simulators to help researchers and developers for selecting the most appropriate simulation tool depending on selection criteria. Moreover, a detailed discussion with the recommendation for best practice in LBS simulation tools is also included in this paper, which would surely help new researchers to quickly identify the most suitable simulator according to their research problem.
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© 2020, IJCERT All Rights Reserved https://doi.org/10.22362/ijcert/2020/v7/i11/v7i1101 1
International Journal of Computer Engineering in Research Trends
Multidisciplinary, Open Access, Peer-Reviewed and fully refereed
Research Paper Volume-7, Issue-11, November 2020 Regular Edition E-ISSN: 2349-7084
A Comparative Study of Location Based Services
Simulators
Rida Qayyum1*, Hina Ejaz2
1*Department of Computer Science, Government College Women University Sialkot, Pakistan
2 Department of Computer Science, Government College Women University Sialkot, Pakistan
e-mail: ridaqayyum6@gmail.com1*, hinaejaz299@gmail.com2
Available online at: http://www.ijcert.org
Received: 07/11/2020 Revised: 12/11/2020 Accepted: 16/11/2020 Published: 18/11/2020
Abstract:- Location-based services are now extremely prevalent due to their massive usage in current and
emerging technologies. The use of simulation tools has been gaining popularity in the domain of LBS systems,
where researchers take advantage of simulators for evaluating the behavior and performance of new architecture
design. This popularity results from the availability of various powerful and sophisticated LBS simulators that are
continuously verifying the flexibility of proposed models of LBS research projects. Despite its popularity worldwide,
there is still a problem for researchers to choose the best simulator according to their needs and requirements,
which provide them accurate results. Furthermore, conducting research on the physical LBS environment for
individuals or small educational institutes is very challenging due to the cost involved in setting up location-based
services live. Therefore, for selecting an appropriate LBS simulator, it is important to have knowledge of
simulators that are currently available along with their features and selection criteria considered for conducting
research in a particular type of problems in the LBS system. In the current study, we have presented various
simulators that provide a cost-effective way of conducting LBS research projects. This paper compares 10
simulators to help researchers and developers for selecting the most appropriate simulation tool depending on
selection criteria. Moreover, a detailed discussion with the recommendation for best practice in LBS simulation
tools is also included in this paper, which would surely help new researchers to quickly identify the most suitable
simulator according to their research problem.
Keywords: Location-based Services, LBS Simulators, Riverbed Modeler, Network-based Generator, Trace
Generator, SUMO, Siafu, GeoLink, GTMobiSim, MobiREAL, GIS, NS3.
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1. Introduction
Recent years have witnessed the emergence of
location-based services systems due to the high availability
of smartphones, wireless communication, and GPS
technologies [1]. Despite the fact, still, there are too many
demandable issues that need a meaningful amount of
research to be done [2]. For establishing LBS research, it is
unattainable for small to large education institutes and many
other organizations to maintain a physical LBS System [3].
There is no specification to perform standard experiments,
which are repeatable, expandable, and dependable
environments using realistic plots and real-world scenarios.
Here, all these problems are to use simulators, which could
imitate real-life physical situations. It is a process of
recreation of a real-world process in a controlled
environment [4].
LBS systems strongly believe in the use of
simulations to understand complex matters in a short time.
These simulators show different kinds of operations by
establishing nodes, virtual vehicles, maps, areas of fixed size,
mobility traces of humans and automobiles, and many other
services that can be designed, making it easier to analyze for
LBS [5]. For this purpose, many simulators have been
Rida Qayyum et.al, A Comparative Study of Location Based Services Simulators”, International Journal of Computer
Engineering In Research Trends, 7(11):pp:1-12, November-2020.
© 2020, IJCERT All Rights Reserved https://doi.org/10.22362/ijcert/2020/v7/i11/v7i1101 2
constructed and are being passionately used by researchers to
conduct LBS research. These simulators diversify in various
fundamental features like programming languages, GUI,
licensing, types, focus, extensibility, deployment mode,
simulation time, visualization, etc. In literature [2, 10, 14, 22,
26, 28, 32, 36], several research papers already considered
some LBS simulators. It is essential for LBS researchers to
wisely select a good simulator that provides a user-friendly
interface, open-ended in modelling, enable smooth
modification, and include appropriate analysis of simulation
output and analytical accuracy of results. Thus, simulation
technology acceptance will widely spread in the IT
community [43, 44]. The advantages provided by simulators
over the development of a real LBS system are:
Reduced Wages: Simulation tools do not require
any purchase of hardware or proprietary software
and nor even maintenance costs. Basically, no
capital investment involved. In fact, several
simulators are freely available that help in
evaluating new protocol design.
Repeatable and Controllable: We can check our
experimental set up as much as we need before our
desired performance is obtained. It helps the
researcher to change input very easily as when
needed, which provides better results as an output.
Also, it can help in understanding how the system
works [6].
Environment: A simulator offers an opportunity to
test various scenarios under different workloads.
The risk with design or any parameters could be
evaluated at an earlier stage through simulation [7].
Hence, a simulation model helps us to gain
knowledge about the improvement of the system.
The primary challenge for researchers is to pick the
best simulator for their LBS privacy-related research as there
are many simulation tools available for specific purposes like
Riverbed Modeler Academic Edition for the road network
[2], SUMO for vehicular mobility [8], network-based
generator for spatiotemporal data [9], and NS3 for user-based
authentication protocol [10], etc. Further, to address this
problem, we concentrate on existing LBS simulators that are
used in the LBS System for many research problems.
In the current study, we have conducted a
comparative analysis of various LBS simulators to help
researchers in choosing a simulator according to the nature of
the issue as there are many diverse simulators present for
certain natures of research issues. Moreover, we have
presented comprehensive study of these LBS simulators
based on diverse criteria and presenting their features and the
detailed description which empower new researchers to
select a relevant LBS simulator. After comparison, the
Riverbed Modeler Academic Edition is suggested according
to its attributes and demand in the LBS research community.
Moreover, as a general purpose simulator, we suggest
Thomas Brinkhoff Network-based Generator of Moving
Objects based on its commercial use and visualization in the
research and development communities. Hence, these
promising solutions help researchers for the right selection of
LBS simulators according to their research problem.
Rest of the paper is organized as follows, Section II
highlights various simulators used in LBS research. In
section III, we have conducted a comparative analysis of
popular LBS simulators based on the evaluation criteria.
Section IV explains discrete criteria that were used to
perform a comparative analysis of LBS simulators. Section V
provides the discussion of the comparative analysis and some
specific recommendations for best practice in LBS research.
Finally, Section VI concludes research work with future
directions.
2. LBS Simulators
In order to provide a better understanding of LBS
simulators, we have discussed various simulators that are
being widely used to conduct LBS research in a simulated
environment. Around 10 LBS simulators had been discussed
in this section.
2.1 Riverbed Modeler Academic Edition
Riverbed Modeler Academic Edition is the most
popular and powerful simulation tool available for the LBS
environment. Its old name is OPNET (Optimized Network
Engineering Tools). In 1986, it was originally developed at
the Massachusetts Institute of Technology (MIT) and used as
a commercial tool for modeling and simulation. Riverbed
Modeler renders modeling scalable simulation and detailed
analysis of a wide range of wired and wireless networks [11].
This is the fastest simulator to analyze and design
communication networks. It provides a virtual network
environment that models the behaviour of an entire network
including its switches, routers, servers, protocols, and
individual applications. It model technologies, protocols, and
devices, then simulate wired and wireless networks of
realistic state and fastly analyze simulation results. Also,
evaluate the performance of a proposed network with the
help of simulation and transmitting real-time traffic.
Riverbed Modeler is an open-source, freely available
simulation tool that is too simple to handle and providing a
user-friendly interface and customizable presentation of
simulation results to the research & development community.
In LBS System, the Riverbed Modeler Academic Edition
17.5 widely used for performance modeling and evaluation
of proposed techniques in local and wide-area networks [2].
Rida Qayyum et.al, A Comparative Study of Location Based Services Simulators”, International Journal of Computer
Engineering In Research Trends, 7(11):pp:1-12, November-2020.
© 2020, IJCERT All Rights Reserved https://doi.org/10.22362/ijcert/2020/v7/i11/v7i1101 3
It interpreting output data by constructing complex network
topologies, simulate the message sending/receiving, and
fixed a region A of size {N km × N km}. Moreover, assign
n ×n nodes as sensitive or ordinary locations for simulating
the LBS environment [12]. Figure 1 demonstrated the
overview of Riverbed Modeler Academic Edition.
Figure 1. Overview of Riverbed Modeler Academic Edition
2.2 Network-based Generator of Moving
Objects
Network-based Generator was developed by
Thomas Brinkoff in 1999 for generating moving objects
applying a real road network. This generator combines
absolute data from the actual road network with user-defined
parameters and produces the data. This is one of the few
generators that allow the visualization of the data and the
road network [13]. This generator was developed in Java and
available as a Java applet. Network-based generator control
by parameters, configuration file, and open-source Java
classes. The graphical user interface of the generator helps in
the parameter’s setting, the visualization of the network of
the created objects [15]. We can specify various features like
maximum speed, maximum capacity of a road in it and
simulate real-life scenarios like bad weather, building
construction on roads, etc. Moreover, we can also add
external objects or rectangles wherever we want [14]. For the
evaluation of spatiotemporal data, the network-based
generator of moving objects was designed. The moving
objects follow roads, railways, rivers, channels, pedestrians,
migration of living objects. Simple text files specified the
network which is used by the generator. For evaluation of the
proposed solution in the LBS system, Network-based
Generator of Moving Objects is broadly used to set up the
moving objects [16]. The generator uses a road map of the
Oldenburg County of region area of 23.57km × 26.92km, a
city in Germany as the input, and it uses the default setting of
the generator for changing the speed of moving objects.
Figure 2, shows the global view of the map of Oldenburg
with the footprints of mobile users. In our opinion, this
generator is the best Spatio-temporal data generator out
there.
Figure 2. Graphical User Interface of Network-based
Generator
2.3 SUMO (Simulation of Urban Mobility)
SUMO is designed as a road traffic simulation for
vehicular mobility to deal with a very large number of nodes
in road networks. In 1998, it was developed by the German
Aerospace Centre and written in object-oriented
programming C++, Java, and Python. It has many
fundamental features, consisting of single-vehicle routing,
collision-free vehicle movement, multi-lane streets with
changing of lanes, right-of-way rules based on the junction,
an openGL graphical user interface (GUI), and dynamic
routing. It's an open-source freely available, highly portable
simulation tool that integrates with openstreetmap.org [17]
Rida Qayyum et.al, A Comparative Study of Location Based Services Simulators”, International Journal of Computer
Engineering In Research Trends, 7(11):pp:1-12, November-2020.
© 2020, IJCERT All Rights Reserved https://doi.org/10.22362/ijcert/2020/v7/i11/v7i1101 4
and target map to simulate traffic with a large number of the
map of the globe for better understanding. SUMO
incorporates helping tools, which handle tasks such as
finding the route, visualization, network import, and
emission calculation. Also, it provides discrete APIs to
remotely control the simulation and it can be increased by
custom models. SUMO is just not a traffic simulator, its
package contains a set of applications that require a road
network and demand for traffic to prepare and perform traffic
simulation [8] as depicted in Figure 3. In the LBS
environment, SUMO can verify the importance of the
proposed model by adopting real-world mobile vehicle traces
and managing a large number of streets. To simulate
vehicular traffic in the real-world environment, the region
map of Northwest Atlanta having information about street
nature, the number of lanes, speed constraints could be
carried by SUMO from the geo-data origin and evaluate the
recommended mechanism using SUMO simulator with real
map Northwest Atlanta region. We can perform manipulation
by covering a large scale area of {N km × N km} and over
10,000 moving vehicles at fluctuating speeds. We use and
extend the SUMO simulator to generate feasible mobility
traces for e-vehicles [18].
Figure 3. Graphical User Interface of SUMO
2.4 Trace Generator
The Trace Generator was developed to model
moving vehicles on roads for large scale computing industry
and to trigger requests from the simulation using the detailed
location information. For this purpose, it uses real-world
traffic data collected in the USGS [19] format from the
National Mapping Department and uses a transportation
layer of 1:24K Digital Line Graphs (DLGs) as road data [29].
For input, using Global Mapper Software to translate the
maps into Scalable Vector Graphic format and retrieve
different types of routes from the original track, grade 1
(expressway), grade 2 (armorial path), and grade 3
(collector). The generator measures the overall number of
cars in various road groups using actual vehicular traffic
records [30]. The total number of vehicles in a given class of
roads is proportionate to the total road length, which is
inversely proportional to the average speed of the vehicles in
the class of roads. After deciding the number of vehicles
along-route type, they are shifted into the graph, and
simulation is begun where cars travel through the roads and
select other highways as they exit. The simulator aims to
ensure that the fraction of the cars is constant overtime on
each type of road. The cars at each joint adjust their speeds
according to a normal circulation whose parameters already
input to the trace generator [31]. It used a map from the
Chamblee region of the state of Georgia in the USA to
generate the trace used in order to evaluate the proposed
solution in the LBS environment. The map loaded into the
trace generator will be shown in Figure 4. The area of the
map is 160 km2. As per road frequency, the 1st grade is 7.3%
of overall highways, while the 2nd and 3rd grade highways
are 5.4% and 87.3%, respectively [32]. Throughout the
simulation, each car produces a variety of messages.
Figure 4. Graphical User Interface of Trace Generator
Rida Qayyum et.al, A Comparative Study of Location Based Services Simulators”, International Journal of Computer
Engineering In Research Trends, 7(11):pp:1-12, November-2020.
© 2020, IJCERT All Rights Reserved https://doi.org/10.22362/ijcert/2020/v7/i11/v7i1101 5
2.5 MobiREAL
MobiREAL is an innovative network simulator that
was developed in C++ object oriented language. It is used for
simulating humans and automobile’s mobility and facilitates
them to change their behavior according to the given
application context. Using this simulation tool, we can
evaluate the definite performance of infrastructures, network
applications, and routing protocols that numerous existing
simulators cannot evaluate well. It can efficiently define the
mobility of objects with the C++ programming language.
Moreover, it follows a rule-based probabilistic model to
express the performance of mobile nodes, which is mostly
used in cognitive modeling of human behavior [22].
MobiREAL simulator comprises two main parts called
MobiREAL behavior simulator which is used to simulate
mobile nodes behavior and MobiREAL network simulator
that helps to simulate data transfer between mobile nodes.
These two behavior and network simulators are independent
programs that systematically exchange significant data over a
TCP channel [23]. It also has an animator that visualizes
packet propagation, network topologies, and node
positions/movements. Figure 5, presents the outcome of the
simulation visualized by MobiREAL animator. To check out
the robustness of the suggested method in the LBS
environment, the network simulator MobiREAL can be
employed to simulate the movement of actual users and fake
locations [24]. For this purpose, shaped a road network in
Kyoto, Japan, and simulates movements of users based on
five real trajectories of normal people collected from the
route lab. This proposed solution allows us to define how
nodes modify their terminal point, routes and
speeds/directions according to their positions, environments
information obtained from application.
Figure 5. Graphical User Interface of MobiREAL
2.6 GeoLink
GeoLink is an open source simulator provides
interactive user interface by showing a map of Digital City
Kyoto [25]. In the map, there is a number of links of public
places in the map of Kyoto, Kaoru Hiramatsu develops this
map and it holds 5400 pages relatively. These public spaces
like shopping malls, hospitals, schools, bus stations,
restaurants, etc are present in an individual map. Moreover,
real-time auditory data is also shown on map that consists of
bus chart, traffic updates, weather status, and live video from
the animated organizations. More than 300 sensors have
already been equipped in Kyoto. It collected traffic data of
more than 600 city buses. Every bus delivers its source and
destination path and also route data after a few minutes. Such
an influential message causes the liveliness of a digital city.
As shown in Figure 6, GeoLink can visualize how web pages
relate to physical locations distributed throughout the city.
GeoLink have both the geographical attributes found in a real
city and the online attributes found on the Internet. GIS, VR,
social agents and animations are the latest technologies of the
time and the city Kyoto was created on these bases. For cost
reduction techniques proposed in the LBS system, the
GeoLink Kyoto service used in the analysis [26]. This
displays many web pages of different spots in city Kyoto and
has a database that incorporates the ID, name, position
including longitude and latitude, URL, address, category, and
a remark of each spot. A geographical database was used to
incorporate various information detail. The dynamism of
moving objects such as avatars, cars, agents, buses, trains,
and helicopters determines a few of the dynamic activities in
the cities. Communityware mechanisms are enforced to
reassure communication in digital cities.
Figure 6. Graphical User Interface of GeoLink Kyoto
Rida Qayyum et.al, A Comparative Study of Location Based Services Simulators”, International Journal of Computer
Engineering In Research Trends, 7(11):pp:1-12, November-2020.
© 2020, IJCERT All Rights Reserved https://doi.org/10.22362/ijcert/2020/v7/i11/v7i1101 6
2.7 Siafu
Siafu is an open-source simulator based on a Java
agent that is used to simulate mobile events in a city. It was
originally developed by Miquel Martin working at the NEC
European Research Lab within the MobiLife project. The
simulator has a graphical interface for displaying and
exporting simulation data [27]. The development of agents is
manual in Siafu, making it more suited for small, basic
situations that can be displayed via an interactive interface.
Figure 7 depicts the simulating agents, maps within the
scenario. In 2007, Siafu became a commercial, versatile,
large-scale context simulator tool that simulated models for
agents, places and the context therein. On the other hand,
Siafu is interesting in the experimental scenarios proposed in
the LBS research work by providing a way to quantify and
analyze defined parameters into some environments within
each scenario. In order to evaluate the performance and
behaviour of new scheme proposed in the LBS System, the
researchers and scientists can employ Siafu, the context
simulator for generating users’ locations by imitating real-
life physical situations as it can help in preserving real
identity of LBS mobile user from disclosure [28].
Figure 7. Graphical User Interface of Siafu
2.8 GTMobiSim
GTMobiSim is uniquely build for creating mobility
traces and query traces for an immense number of mobile
devices traveling over a road network with the uses of maps
present at the National Mapping Division of the USGS [19].
It is only used for academic and non-commercial purposes.
GT Mobile Simulator driven by an XML configurations files,
enables various mobility models on road networks, locations
of mobile objects at any time instance, the ability to specify
various parameter distributions, and generate query traces. In
the LBS System, the performance of proposed privacy
protection approaches could be evaluated by using
GTMobiSim. To perform the experiment in GT mobile
simulator, firstly implement the scheduled approach in a java
programming language which is used to develop a trace of
moving vehicles on a realworld road network, retrieve
from maps accessible at the national mapping division of the
Simplified gateway selection (SGS). This simulator uses road
networks established with three types of roads i.e.
expressway, collector roads, and arterial [20]. There are 3
geographic regions maps that are used for experimentation,
Chamblee and Northwest Atlanta, regions of Georgia and
San Jose West, region of California to generate indications
for designated hour’s duration. There is a set of 10,000 cars
on the road network that are aimlessly located according to
an orderly distribution. Routing is used to direct the cars for
random tours. The speed of the cars is appropriated depend
on the lane class [21] as demonstrated in Figure 8.
Figure 8. Graphical User Interface of GTMobiSim
2.9 Network Simulator (NS3)
Network Simulator (NS3) is free and open-source
software used for small scale computing industry. It was first
released in 2008. Tom Henderson supported the growth of
NS3 by collaborating with the US National Science
Foundation (NSF). NS3 is a standalone simulator licensed
under GNU GPLv2. Its latest version was launched in
February 2015 as an NS3.22. It is a network simulator that
has a simple GUI that helps you to virtually create a network
that consists of devices, applications and links as shown in
Figure 9. It enables researchers to create network scenarios,
design protocol, perform analysis, and model traffic and
study the interaction between various network devices [38].
By using NS3 in the LBS system, it is possible to study
system behavior in a highly managed environment and
analyze how the system works. It has an efficient user-based
Rida Qayyum et.al, A Comparative Study of Location Based Services Simulators”, International Journal of Computer
Engineering In Research Trends, 7(11):pp:1-12, November-2020.
© 2020, IJCERT All Rights Reserved https://doi.org/10.22362/ijcert/2020/v7/i11/v7i1101 7
authentication protocol for the LBS system over road
networks. NS3 [39] can used to improve LBS mobile user’s
authenticated key by establishing protocol that has shorter
time manner, shorten wages, minimize packed data loss and
ensure privacy protection as compared to existing state-of-
the-art network simulators [40].
Figure 9. Graphical User Interface of NS3
2.10 Geographical Information Systems
(GIS)
Geographical Information Systems (GIS) is
uniquely built for providing geographic information services
to LBS systems via the internet or mobile-networked
environments. It is an open-source information system that is
used to manipulate, update, and analyze the spatial and
geographic data by presenting them as maps [33]. Both
online map services and GIS can be considered important for
LBS systems. Its five common components are hardware,
software, models, data and people for spatial analysis. As
shown in Figure 10. GIS technology combines standard
database processes with the exclusive visualization and
spatial interpretation advantages that maps offer with these
inquiries and statistical analyses [34].
Figure 10. Convergence of GIS technology for LBS
There are further 3 types of GIS as follows:
Desktop GIS: It represents data on desktop and
limited to the desktop computer. ArcGIS Desktop
(ESRI), envision (Autodesk), MapInfo Professional
is the Desktop GIS software [36]. GRASS GIS and
Quantum GIS are the free and open-source desktop
GIS software. Figure 11 shows the GUI of
Geographical Information Systems (GIS). Due to its
limitation to desktop PC and not access remotely, it
is not very suitable for LBS.
Web GIS: It is a distributed information system that
is used to integrate and communicate geographic
information over the World Wide Web [35]. Also
provide the advantage of global reach, a large
number of users, better platform compatibility, easy
to use and low cost as averaged by the number of
users. Due to diversity nature, distributed data over
the internet. Hence, web GIS is suitable for LBS.
Mobile GIS: Mobile GIS is a merged software and
hardware structure for access to geospatial data and
activities through mobile devices via wired or
wireless networks in LBS [37].
GIS address many state of the art research
challenges around LBS. For conducting research in LBS
domain, researchers can develop a system which uses GIS
tools and integrates heat map to preserve the spatial
information of mobile user [45]. In order to explore the
implications of the emerging geographic information system,
researchers can consider a new form of geospatial data for
the implementation of advance modeling techniques in LBS.
Figure 11. Graphical User Interface of GIS
Rida Qayyum et.al, A Comparative Study of Location Based Services Simulators”, International Journal of Computer
Engineering In Research Trends, 7(11):pp:1-12, November-2020.
© 2020, IJCERT All Rights Reserved https://doi.org/10.22362/ijcert/2020/v7/i11/v7i1101 8
3. Comparative Analysis of LBS
Simulators
In this section, we have made a comparative
evaluation of various LBS simulators based on the diverse
evaluation criteria. The parameters for comparison were
chosen based on many researchers' previous work. Table 1,
presents a summary of the analysis. Based on the research
objective, this comparative study on LBS simulators enable
researchers to choose a simulator according to the nature of
the issue as there are numerous simulators geared for specific
types of research problems.
Table 1. Comparative Analysis of LBS Simulators
Simulators
Availability
Programming
Language
Networking
GUI
Simulation
Type
Deployment
Mode
Visualization
Focus
Map
Riverbed
Modeler
Python
Full
Academic
Enterprise
Preserve Identity,
Spatiotemporal
information
User-defined
Network-based
Generator
Java
Full
Commercial
Large Scale
Preserve
Spatiotemporal data
Real
Trace
Generator
Java
Limited
Open Source
Large Scale
Preserve Identity &
Spatial Information
Real
SUMO
C++, Java,
Python
Full
Commercial
Enterprise
Preserve Identity &
Spatial Information
Real
Siafu
Java
Limited
Open Source
Large Scale
Preserve Real
Identity
Random
MobiREAL
C++
Full
Commercial
Enterprise
Preserve identity &
Spatial information
Real
GeoLink
Java
Limited
Open Source
Large Scale
Preserve Spatial
information
Real
GTMobiSim
XML, java
Full
Commercial
Enterprise
Preserve Spatial
information
User-defined
GIS
Python,
C++, Visual
Basic & JS
Full
Open Source
Large Scale
Preserve Spatial
information
Real
NS3
C++,Python
Full
Open Source
Small Scale
User-based
authentication
None
4. Evaluation Criteria
In this section, we have introduced several
evaluation attributes based on which comparative analysis is
performed. Table 1 compares the most popular simulation
tools [41, 42] for LBS Systems in terms of Availability,
Programming Language, Networking, GUI, Simulation time,
Simulation Type, Deployment mode, Visualization, Focus,
and Map. The parameters for comparison were adopted
based on many researchers' earlier work [2, 10, 11, 14, 16,
18, 20, 26, 28, 32, 38] and are as follows:
Availability: This attribute defines whether the simulator
is available for download and use or not. Freely available
simulators are those whose source code is under public GNU
license and is available for community use. Table 2, contain
availability sites of each simulator mentioned in the previous
table.
Table 2. Simulation Tools Availability
LBS Simulators
Availability (sites)
Riverbed Modeler
Free for academic & non-profit use
https://cms-api.riverbed.com/portal/community_home
Network-based
Generator
For commercial use
https://iapg.jade-hs.de/personen/brinkhoff/generator/
Trace Generator
Free for use
https://www.usgs.gov/
SUMO
For commercial use
https://www.eclipse.org/sumo/
Siafu
Open Source
http://siafusimulator.org/download/
MobiREAL
For commercial use
http://www.mobireal.net
GeoLink
Open Source
http://geolink.sourceforge.net/
GTMobiSim
For commercial use
https://code.google.com/archive/p/gt-mobisim/downloads
GIS
For Free use
https://qgis.org/en/site/forusers/download.html
NS3
Open Source
https://www.nsnam.org/releases/ns-3-29/download/
Rida Qayyum et.al, A Comparative Study of Location Based Services Simulators”, International Journal of Computer
Engineering In Research Trends, 7(11):pp:1-12, November-2020.
© 2020, IJCERT All Rights Reserved https://doi.org/10.22362/ijcert/2020/v7/i11/v7i1101 9
Programming Language: This attribute specifies the
programming language the simulator used for development.
Most LBS research needs improvements to the underlying
simulator architecture which has been built through a certain
programming language.
Networking: Networking support is crucial to perform
simulation for the LBS system. This parameter informs us
whether the simulator upholds networking or not. Also, this
aspect informs us to what extent the simulation tool supports
networking either full, limited or no connectivity.
Graphical User Interface (GUI): The scope of GUI has
an important part in the simulation environment and supports
the researchers in a way so that they can efficiently execute
their simulations in a smooth and productive way. This
characteristic confesses whether a simulator grants a GUI or
not.
Simulation Time: This aspect expresses researchers how
much time a simulator takes to execute the simulation and
display the appropriate outcomes. If a simulator takes more
time, it portrays that the simulator is ineffective.
Simulation Type: This parameter present whether the
simulator is open source which means free for use and
anyone can easily access it for research purpose or it is
available for only commercial use or just you can use it to
fulfil academic goals.
Deployment mode: Current research trend in the LBS
system is concerned with the deployment mode of the
simulator i.e., enterprise, small and large scale. So, it is
important to know the simulator deployment mode to
efficiently perform a simulator according to the nature of the
research project in the LBS System.
Visualization: Another research trend in the LBS System
is to determine the effectiveness of the simulation tool in
terms of visualization. Most of the simulators satisfy
performance parameters well in respect of the requirement
for which they have developed. This attribute tells us which
simulator focuses on visualization or not.
Focus: This parameter specifies the purpose and outcome
the researchers expect after their implementation in LBS
simulators. So, with the uses of these simulators in the LBS
system, the researcher can work on the privacy issue of LBS
where users can hide their personal data by preserving their
identity and spatiotemporal information from the malicious
user.
Map: This parameter defines what type of map simulator
uses to perform the simulation for the LBS system. Map
could be user-defined, real, any random map of areas, or
none of the map is used to perform the simulation. This
evaluation factor signifies whether the simulator allows
researchers to use real-world information obtained from the
map or not.
5.Discussion & Recommendation
The current study highlighted the problem faced by
researchers and scientists to choose a credible simulator for
conducting research in the Location-based services system.
Several LBS simulators have been studied for this purpose. In
this section, firstly we present a detailed discussion on the
comparative analysis of various simulators of LBS based on
the evaluation criteria specified in the previous section. Then,
describe important recommendations that add scientific rigour
to the simulation process for researchers to perform
benchmarking experiments on simulators for completing their
LBS research tasks. However, the primary findings
highlighted in the study are listed down and the brief
description of the analysis is described in Table 1.
It is observed from the table that 86% simulators are
currently available for conducting research on the LBS
system. The availability of these simulation tools enables the
researcher to simulate real-life physical situations in a
controlled environment. It also observed that almost 67% of
simulators were developed in the Java programming
language. The second primary programming language is C++
and Python for the development of these simulation tools
mentioned in table 1. Only GIS simulator was developed
using SQL, Visual Basic, and JavaScript. Moreover, almost
73% of simulators support networking. One adverse
consideration is that only 31% of the simulators contribute
finite networking for research on LBS. The availability of
graphical user interface (GUI) fascinates a higher number of
researchers to operate the simulator. It is noticed that almost
76% of simulators have a user-friendly GUI. On the other
hand, only 37% of the simulators arrange full to finite GUI
for researchers. Regarding the simulation time,
approximately 82% of simulators operate in seconds. The
simulators that can perform simulation in minutes are Siafu,
Trace generator, and Network-based generator for moving
objects by Thomas Brinkoff.
In this paper, there are three types of simulators,
among these 50% to 60% simulators are open source which
means free for use, you don’t need to purchase or pay for
them. The rest of the simulators are for commercial or
academic purposes according to researchers' needs. The
aspect of deployment mode is important for researchers to
know about the desired results. 45% simulators are working at
large scale and enterprise level computing industry and 10%
are used at small scale computing industry like NS3.
Additionally, LBS system determines the effectiveness of the
Rida Qayyum et.al, A Comparative Study of Location Based Services Simulators”, International Journal of Computer
Engineering In Research Trends, 7(11):pp:1-12, November-2020.
© 2020, IJCERT All Rights Reserved https://doi.org/10.22362/ijcert/2020/v7/i11/v7i1101 10
simulation tool in terms of visualization. It is observed that
almost 80% to 83% simulators are excellent at visualization,
rest 20% to 17% for example GeoLink and trace generators
are not good enough to support visualization. Regarding the
focus of simulators, researchers can hide the personal
information of LBS user by considering riverbed modeler,
network-based generator, GTMobiSim, and many others
which are used to preserve identity and spatiotemporal
information. On the other hand, NS3 focuses on user-based
authentication protocol. The availability of maps plays a
fascinating role in LBS research, 60% of the simulators use
real-world maps like SUMO and MobiREAL. While 20% of
maps are user-defined according to the user's choice and the
rest 20% are using just random maps.
Eventually, it is worth to mention about some of
special purpose LBS simulation tools. Mobile GIS is the only
simulator that enables researchers to observe the performance
of the LBS system using real applications with wireless
networks that need computationally intensive devices with
large display screens. Riverbed Modeler Academic Edition
and Thomas Brinkhoff Network-based Generator of Moving
Objects are the only simulators that enable researchers and
scientists to execute the performance of LBS techniques over
road networks. SUMO is the only simulator that supports
vehicular mobility for generating traces for humans and
automobiles. NS3 is the only simulator that grants research
efficient user-based authentication protocol in LBS whereas
all simulators discussed in the literature section address
privacy-related aspects in the LBS system. We suggest
riverbed Modeler academic edition according to its
characteristics and demand in the LBS research community.
Moreover, as a general purpose simulator, we recommend
Thomas Brinkhoff Network-based Generator of Moving
Objects based on its commercial use and visualization in the
research and development communities. Hence, these
promising solutions help researchers for the right selection of
LBS simulators according to their research problem. In this
paper, we provide some specific recommendations.
Specifically, LBS researchers should: (1) choose a good LBS
simulator according to the type of problem they are
addressing in their research work; (2) Wisely choose
statistical approaches in order to reduce the number of
simulations and to analyze the simulation results. Adopting
these suggestions will help to choose a credible simulator for
research on the LBS domain.
6. Conclusion
Simulation technology is increasingly popular
among researchers worldwide in recent years. The aim of the
research carried out in this paper is to enhance the knowledge
of LBS simulators among researchers. This paper discussed
LBS simulators' advantages better to understand the real-life
physical environment in a short time. This paper's innovative
work considers the latest LBS simulators such as Riverbed
Modeler Academic Edition, Network-based generator,
SUMO, MobiREAL, and GTMobiSim, and many others. All
of the 10 LBS simulators have been compared based on ten
evaluation criteria: availability, programming language,
networking, GUI, simulation time, simulation type,
deployment model, visualization, focus, and map. The current
research presents detailed discussion and recommendations
based on a comparative study, which empowers new
researchers to select a relevant LBS simulator. Although there
are many LBS simulators available, we can say that picking a
suitable simulator according to the type of problem is very
important. There are numerous simulation tools geared for
certain types of research problems in the LBS system. The
current study suggests Riverbed Modeler Academic Edition
based on its features and popularity in the LBS research
community based on critical analysis. Moreover, as a general-
purpose simulator, we suggest Thomas Brink off Network-
based Generator of Moving Objects based on its commercial
use and visualization in the research and development
communities. Hence, these promising solutions help
researchers select LBS simulators according to their research
problem.
Acknowledgements
This work was performed under auspices of
Department of Computer Science and Information
Technology, Government College Women University Sialkot,
Pakistan by Heir Lab-78. The Authors would like to thanks
Dr. Muhammad Usman Ashraf for his continuous support,
enthusiasm, insightful, and constructive suggestions
throughout the research.
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Authors Profile
Rida Qayyum (born September 17, 1996)
received BS-Information Technology
(BSIT) degree in 2019 from Government
College Women University Sialkot,
Pakistan. She has awarded with Gold
Medal and Roll of Honour for her
academic performance in BS-Information
Technology from GCWUS and certified
as Microsoft Office Specialist. She has many publications in
international journals. Her research on Location Based
Services Systems, Mobile Cloud Computing, and Big Data
has appeared in International Journal of Advanced Research
in Computer Science, International Journal of Advanced
Computer Science and Applications, International Journal of
Computer Engineering in Research Trends, I.J. Modern
Education and Computer Science, I.J. Education and
Management Engineering and I.J. Wireless and Microwave
Technologies. She has served as HPC scientist in High
Performance Computing Research Centre.
Hina Ejaz (born March 25, 1997) is
currently student of BS in Information
Technology (BSIT), Department of
Computer Science from Government
College Women University, Sialkot. Her
research interest including Location
based services System, Network Security,
Telecommunication System and
Computer Communication Network.
... This scheme offers a strong load balancing, low overhead and cost connectivity with increased privacy level in LB-ISA. Thus, this scheme doesn't provide adequate privacy to identity-related information and data query protection [36]. ...
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Road traffic information has become indispensable for routine vehicular communication but user location privacy an important issue which did not well addressed. An adversary may attack a user by tracking location in routine vehicular communication. Although, continuously changing pseudonyms is a promising solution to attain location privacy in road networks, it has been observed that changing pseudonym at improper time or location may again become a threat for location preservation. As a result, a number of techniques for pseudonym-change have been proposed to achieve location privacy on road networks but most of location based services depend upon speed, GPS position and direction angle services. Hence, sensitive information is periodically broadcasted in every 100-300 ms providing an opportunity to adversaries for accessing critical information and easily tracking vehicles. Moreover, existing methods such as RPCLP, EPCS and MODP for attaining location privacy in mix-zones environment have severely suffered due to large number of pseudonym-changes. To cope with these issues, we presented a Dynamic Pseudonym based Multiple Mix-zones (DPMM) strategy to acquire the highest level of accuracy and privacy. The concept of executing dynamic pseudonym change has been forwarded with respect to pseudonyms, velocity and direction of moving objects. We performed our simulations by using one SUMO simulator and analyzed results compared with existing pseudonym-changing techniques. Our simulation results outperformed various existing techniques and provided better results for achieving high privacy rate, requiring small number of pseudonym-change as well as providing best performance.
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