Systematic Review: Fog Computing in Education IoT Systems

This report presents a systematic literature review on enabling technologies for fog computing within New Zealand higher education IoT systems. The study investigates the application of fog computing to enhance educational facilities, improve scalability, security, and data management. It explores the architecture, objectives, and methods used to improve the performance of education applications, addressing limitations and challenges. The research methodology includes identifying requirements, defining research gaps, and conducting a literature review. The paper discusses the current education system, objectives fulfilled by fog computing, and methods used to enhance application performance. Key findings include the benefits of fog computing in improving data access, security, and real-time capabilities within educational settings. The report concludes by emphasizing the importance of fog computing in improving education functionalities and providing recommendations for future research.

Enabling technologies for fog
computing in New Zealand
higher education IoT systems
Abstract
Context: Fog computing architecture is referred to the
architecture that is distributed over the geographical area. This
architectural arrangement mainly focuses on physical and
logical network elements, and software for the purpose of
implementing proper network. Fog computing architecture
allows the users to have a flexible communication and also
ensures that the storage services are maintained efficiently for
the purpose of managing the data. However it has been
observed that in the field of education fog computing
architecture has gained huge importance due to its real time
application feature. Objective: The main objective of the study
is developing a systematic literature review for the technology
of fog computing in the education IoT system. The paper will
also focus on evaluating the essential factors that has a crucial
role in the fields of education. The paper will focus on
determining the limitation and findings associated with the
selected topic. Methods: The researches have been carried out
after evaluating all the necessary articles for the purpose of
finding the key concept associated with the fog computing the
education field. Discussion: Fog computing is considered as
one of the most efficient application that has the potential to
improve the educational facilities offered towards the students.
This will offer a better scalability, security and tolerance
towards the educational infrastructure. Learned Lessons:
With the help of proper analysis and research it will become
easy to gain knowledge regarding the fog computing. The
latency will be decreased and this will eventually lead to
hampering the performance. It is very much important to
ensure that the designed IoT system is capable of providing
real time access. Conclusions: The fog computing in the fields
of education helps in improving the business functionalities.
Keywords: fog computing, edge computing, education
I. Introduction
Internet of things offers a wide range of services
with computational facilities. This helps in improving the
way storage capabilities are enhanced in different fields and
also helps in improving the business processes. IoT helps in
staying connected with the objects for the purpose of
sharing and exchanging the data. With the evolution of
technologies it has been observed that the control over the
different applications has reduced to great extent and thus
there is a need to manage the system flow. Cloud
computing has gained huge importance in the fields of
education (Aazam & Huh, 2015). The fog computing
concept was identified with the purpose of determining the
limitations associated that are faced with the use of cloud
computing. The use of fog computing helps in shifting the
capabilities of cloud towards the end user and offers a
better storage capability with enhanced computation
features. The main reason behind using fog computing is
that it offers better communication, enhances privacy,
offers better security and also increases the network
bandwidth so that it becomes easy to match the latency-
sensitive (Akrivopoulos et al.,2018). The concept of fog
computing helps in ensuring that the application designed
has the capacity to satisfy the needs of the education IoT
system.
It has been observed that the performance offered
with the education system and the way lessons are taught
towards the student may get hampered due to low latency
and this will eventually lead to hampering the data shared.
IoT helps in providing a better platform for the students so
that they can easily access the materials from the
communication channel (Parikh et al., 2019). Education
application tends to store huge data related to the students,
staffs and their associated document. Hence there is a need
to manage proper storage so that the data can be organized
properly (Abdel‐Basset et al., 2019). In the fields of
education there are several data stored and retrieved for
daily activities. Thus it becomes essential to integrate
properly the responses that are associated with the IoT
system. The fog computing infrastructure involves
connecting different fog nodes together for the purpose of
improving the scalability, elasticity and the redundancy
(Pecori, 2018). After analyzing the wide range of features
offered with the fog computing it can be stated that, with
the use of fog computing in the educational field it will
become easy to offer the facilities towards the students.
The main aim of the study is too develop a
systematic literature review on fog computing in the fields
of education so that it becomes easy to analyze the
architecture. The literature review will focus on identifying
the problems and challenges that are faced with the use of
IoT systems (Al Faruque & Vatanparvar, 2015). The
second objective of the paper is evaluating the performance
that is offered with the use of fog computing in education
IoT system. The paper is divided into different sections that
include discussing the methodology behind the research
paper, related paper discussion, discussing the role of fog
computing in the education application, identifying the
limitations, providing proper recommendations and last
focus will be on explaining the conclusion (Preden et al.,
2015). The paper will focus on evaluating the different
concepts that are related with managing the education
related data effectively with the use of proper fog
computing implementation.
II. Research methodology
Fog computing is considered as the most efficient
way of improving the efficiency and also ensures that the
amount of data needs to be transported are provided with a
better storage (Okafor et al., 2017). The major steps that are
associated with planning the process for fog computing
implementation in the fields of education application are as
follows: identifying the requirements that are essential for
managing the information related to education, defining
and investigate the gaps that lies in the researches,
improving the procedure for performing systematic
literature review on fog computing in the fields of
education system (Al-Khafajiy et al., 2017). The main

objective is to explore the importance of Fog computing in
Education IoT system. The information needed for
managing the computing process should have the potential
to ensure that the researches have been executed properly.
Research questions
Research questions Motivations
Question 1: what is the
current system of the
education system?
The main architecture of
the current education
system is to offer a better
support towards the system.
However it has been
observed that the education
system fails to maintain the
data effectively.
Question 2: what objectives
are fulfilled using fog
computing?
The key objectives that are
going to be fulfilled with
the use of proper fog
technology is that it will be
capable of managing the
huge amount of data that is
accessed within the
education system.
Question 3: Which methods
are used for enhancing the
performance of education
applications?
State of art is considered as
the best way of determining
the importance of fog
computing in the fields of
education system.
Inclusion and exclusion table:
Criteria Prenominal
Inclusion Using research
articles that are
linked with edge
computing, cloud
computing, IoT
AND fog
computing in the
fields of higher
education
Articles, survey
papers, and
scientific papers
that are associated
with fog
computing
Exclusion No use of books,
non-English
articles and other
topics related
articles
Excluding the use
of non-English
and non-related
articles
A. Study selection
In order to carry out the studies it becomes
essential to review proper study area that will be capable of
managing the data. Before reviewing any article it is
important to ensure that all the concepts related to fog
computing are being analyzed properly (Aldowah et al.,
2015). It is important to ensure that all the related articles
are executed form the list so that it becomes easy to explore
the new knowledge areas related to fog computing in the
education IoT system.
III. Fog computing in education IOT
systems
The main objective of this section is to ensure
that the fog computing has been discussed properly for
providing a better way of demonstrating the importance in
education IoT systems. The IoT systems are used for the
purpose of offering a better connected and collaborative
future towards the education sector (Bagheri & Movahed,
2016). IoT devices have the potential to provide the
students with better access and will also ensure that all the
materials are communicated successfully among the student
so that it becomes easy to provide real time experience
towards them. Governance is considered as the most
important method for the IoT education system. This
ensures that each activity is determined effectively within
the system so that the performance can be enhanced
properly (Banica, Burtescu & Enescu, 2017). Fog based
governance system is going to be developed for the purpose
of providing easy access and management of the data flow
within the education system. This will ensure that the
governance process is executed with low cost. In addition
to this for developing a successful governance system can
be developed with the use of smart gateways and efficient
IoT sensors (Rathna & Shanmugavalli, 2018). The sensors
will be responsible for determining the courses that are
offered towards the students and the key activities that are
performed within the education system. While storing and
managing the data within an education system it becomes
essential to ensure that the data are managed effectively
with proper security and privacy (Atlam et al., 2018). With
the use of fog based application it becomes easy to manage
the data that are accessed between the systems. The fog
oriented system was proposed between the cloud and the
end devices. This provides an intermediate layer.
Every system needs to ensure that proper privacy
and security are introduced within the network for
managing the access. The cloud access security broker
protocol is used for the purpose of organizing the security
between different layers of network (Arora & Kaushik,
2020). This offers a wide range of security policies for the
purpose of improving the features. CASB approach is used
with the help of a modular approach. This model supports
aggregating data from wide range of frameworks. Fog
computing system architecture was designed for the
purpose of managing the raw data associated with the
activities that takes place within the education sector (Basir
et al., 2019). The data identified as crucial are further
forwarded to cloud for better management. With the use of
smart education system it becomes easy to distribute the
data. With the help of advanced system it will become easy
to monitor the activities that are carried out within the
education system. The system will be able to provide better
ability to governance the activities that are carried out
within the system. The fog system has the potential to
remove the issues such as security and reliability factors
(Barik et al., 2017). The education can be offered towards
wide range of students. The three layers that are associated
with the education system include fog layer, cloud layer
and the IoT sensors.
Interactive learning will become easy with the
use of fog in IoT system. The textbooks will be linked with

the web based sites so that it becomes easy to offer better
learning materials towards the students (Amaxilatis et al.,
2017). The study material includes animated videos,
assessment, videos and other materials for enhancing the
learning process. The main aim of using fog computing in
the fields of education is that it will be able to provide
better protection towards the learning courses and other
facilities that are offered towards the students (Bonomi et
al., 2012). This will reduce the need of unwanted
explanation and teacher’s involvement. Fog computes is
being implemented with the aim of providing better way of
communication with the end users. This will offer
interoperability, preprocessing and heterogeneity within the
cloud. It has been observed that the fog computing has the
potential to offer better proximity towards the end users
(Neagu et al., 2018). In addition to this the use of fog
computing also offers decentralized computing so that
better support can be offered efficiently towards the
education system. The quality of services can be enhanced
with the use of fog computing. Thus it can be stated that
with the use of proper technologies it becomes easy to
manage the services. After analyzing the wide range of
benefits that are offered with the use of fog computing it
can be stated that the scalability, mobility, awareness and
reliability increases within the architectural layer (Ni et al.,
2018).
IV. Related works
A. Methods
The method part represents a brief description on
the particular method that developers and analysts need to
follow to successfully implement fog computing in New
Zealand education IoT system. Specific framework or
model discussed here is applicable to enable technologies
for fog computing in education IoT system (Amaxilatis et
al., 2017). The framework is considered as the leading
parameter for those were target of searches use shared fog
nodes, smart gateways in terms of fog nodes. Before
enabling useful technologies for fog computing specifically
in education IoT system the detail architecture of fog
computing should be implemented according to
requirement.
At first, the nodes that are shared within n fog
computing must be planned at the early stage of
development. In order to distribute the decision making
tasks through shared fog nodes and smart gateways the new
edge mesh computer paradigm is used. It is recognized that,
the personal gateways positioned in the student side server
like intermediate nodes (Akrivopoulos et al., 2018). For
processing student oriented data the intermediate node is
generally used. Secondly security of the server must be
maintained accurately by the development team associates.
In order to facilitate the resource sharing between
all the related fog nodes an effective algorithm has to be
applied. How the fog nodes will be connected to individual
education IoT system related applications, for gateways
need to set accurately (Cai et al., 2018). Two different
algorithms are proposed. The first one is to pick the best
applicable fog, whenever users are at the overlapping part.
The second algorithm proposed will help to resolve
situational difficulties (Naha et al., 2018).
In order to enable technologies for fog computing
in the education IoT system the most important part on
which the developers need to keep focus is the fog
architecture. The proposed one is a six layered architecture
comprises of physical or virtual layer, monitoring layer,
preprocessing layer, temporary data storage layer, security
layer and transport layer (Kumar et al., 2019). In order to
earn good academic records implementation of fog
computing in education IoT system is very essential. The
physical or virtual layer is comprises of virtual sensor
network, wireless sensor networks, physical sensors and
virtual sensors. The monitoring layer will conduct all
activities that help monitoring needful operations
(Borthakur et al. 2017).
The monitoring layer operation individually
monitors power supplies, resources, response of the
students and lecturer over education and other services
(Naranjo et al., 2016). The preprocessing layer suggested in
this fog architecture is applicable for data analysis, filtering
data, trimming and reconstruction. The temporary storage
layer of the architecture will distribute and replicate data.
For storage space virtualization the temporary storage layer
will be configured (Cai et al., 2018). Maintaining overall
security is also essential to keep confidential data related to
students and employees secured from external users.
Fog computing is defined as a decentralized
technical infrastructure used to compute, store and apply
data located in the cloud. The advantages of fog computing
is nowhere different from edge computing. For improving
education efficiency fog computing is recognized as to be
very essential (Neagu, 2018). In order to improve overall
security of education IoT system, fog computing is most
effective than any other. Fog computing and Internet of
Things are two widely connected technologies. The
applications where cloud computing is found as not enough
viable, fog computing is used. This specific distributed
approach helps to address the industrial IoT and IoT
requirements (Choudhari et al., 2018). The issues of extra
time consumptions and smart sensor operators get resolved
with implementation of fog computing in the education IoT
system.
It reduces the required bandwidth and also
reduces the back and forth communication present between
cloud and sensors that may negatively impact the
performance of the New Zealand IoT system (Mukherjee et
al., 2017). The net amounts of information sent in the cloud
get reduced in fog computing (Kim, 2019). It helps to
converse the network bandwidth to get better the entire
response timing (Chang, Srirama & Buyya, 2017). The data
confidentiality is maintained than the general cloud
computing technology. It supports the mobility and
minimizes internet latency and networks. However, in
some cases the application may face authorization and data
authentication issues. Apart from that privacy issues can
also occur (Mahmud et al., 2019). Security issues such as
spoofing, man in the middle issue also may occur in case of
fog computing.
Smart electronic education gateways are
integrated in this system to connect individual devices. In
order to preprocess alternatives and other data the

suggested E-Education system is very essential. The
personal gateways used here will act as intermediate nodes
(Basir et al., 2019). In order to give rich and understanding
experiences these days education industry IoT system in
New Zealand is facing major obstacles. Students and
teachers both are needed to have options to access modern
day technologies. Digital focused learning will improve the
teaching and learning process as a whole. In other words
for both trainers and trainees fog computing is essential
(Marquez et al., 2016).
Fig1: Fog computing architectural layer
B. System development
The efficiency of data storing and data accessing
becomes easier and quicker with enabling fog computing in
the education IoT system. These days most of the higher
institutions in New Zealand are implementing regular
office applications, online desktop, messaging services to
hold web level solutions for students and teachers much
specifically. According to (Parikh, Dave, Patel and Doshi,
(2019) the issues of traditional cloud computing and IoT
Technologies also get resolved with application of Fog
Computing because of its lower latency. The response time
in fog computing is lesser than any other immediate
technologies.
The fog computing technology is comprises of
three main work package in terms of method selection,
system development and review through survey. The
method is comprises of detail framework and model. On
the other hand, Zhang et al., (2018) stated that the system
development activity is comprises of architecture and
system that is implemented. Final framework holds shared
fog nodes and smart gateways. A data centered fog
platform needs to be developed at the initial stage of
implementation (Yousefpour et al., 2018). In order to
provide onsite technology that can scale up and down
according to college requirements fog computing enables
important micro data facilities. Even if it is found that the
university lags IT experts can also use fog computing
technology in their education IoT (Chang, Srirama &
Buyya, 2017). In order to build sub network, individual
smart objects are linked up to Fog Edge Nodes. For
building time to time communication fog computing has to
be implemented in education IoT system.
For processing huge dataset firework model is
designed, planned and developed by developers in
cooperative edge environment (Lu et al., 2017). In order to
improve the education IoT system in universities proper
data integrity and security among employees, teachers and
students has to be maintained accurately (Alrawais et al.,
2017). Cloud IoT platform performs horizontal roaming
and vertical offloading migration that are again organized
in three layers protocol. The proposed security scheme is an
end to end architecture. For transmitting both tactical and
non-tactical information this model is much effective and
essential as well (Lee et al., 2015).
Intelligent computations to the smaller and
autonomous units are successfully distributed followed by
this model and framework based application (Kumar et al.,
2019). The inabilities associates to the current education
IoT system got resolved with the implementation of fog
computing in the application (Song et al., 2017). In order to
collect huge set of real time data this particular predictive
model is developed considering cyber manufacturing. The
newly enabled fog computing system would be able to
support IoT education system. IoT system helps
universities to make the education approach much
accessible in geography, status as well as abilities (Liu et
al., 2018).
According to Liu et al. (2018) IoT technology
can be integrated successfully in the university
environment. For building a broader application in
education system IoT gives solid foundation. Immersion is
defined as one of the most powerful mechanisms used to
select and learn best suited foreign language. The secret
weapon for this application is real time feedback generation
(Elmroth et al., 2017). Infact teachers would also be able to
provide real time feedback to the students whenever
required. In order to check whether students have made all
accurate statement selection and usage IoT system stands
beneficial (Kiryakova et al., 2017).
Student’s progress monitoring and performance
analysis become easier and quicker than previous
traditional approach. It helps to connect classroom to form
up a digital presentation (Rauniyar et al., 2016). Special
education, physical education, school operation security,
classroom monitoring and personalized learning become
enabled with this system approach (Atlam, Walters &
Wills, 2018). However, in this paper not only the benefits
but also respective disadvantages associated to this
technology are also elaborated in this paper. The
performance of fog computing in education IoT system is
also evaluated in this paper.

Fig2: Fog computing in Education
C. Review and survey
In order to describe fog computing in education IoT,
firstly different similar articles will be reviewed and survey
accordingly. For protecting data related to students,
teachers and employees as well fog nodes are important as
it can connect other fog nodes (Razouk, Sgandurra &
Sakurai, 2017). In order to gather used information from
various resources similar papers and detail survey is
conducted. Hussain, (2017) stated that, fog computing is a
geographically distributed architecture that can connect
multiple numbers of heterogeneous devices ubiquitously
with the network structure of university. Whether enabling
fog computing in the education IoT system is beneficial or
not is reviewed through survey and secondary analysis.
According to Borthakur (2017), fog computing
processes easy computation, flexible communication
between teachers and students. It also gives faster data
storage and data access abilities to the university associates.
It gives real time response with lower latency (Razouk et
al., 2017). The education process distribution becomes
secured, scalable and distributed in nature after enabling
fog computing technology. In contrast to cloud computing
fog computing stands better (Naha et al., 2018). Data
security, storage and access capabilities of education get
improved with fog computing technology. The Fog
computing technology always works better in IoT
architectures (Dastjerdi et al., 2016). It is reviewed that fog
nodes play important role in fog computing.
Fog nodes help to receive real time data. It also
enables real time analytics applications. System can give
response within milliseconds after introducing fog
computing technology in the IoT applications (Jadeja &
Modi, 2012). However, it provides temporary information
storage unless all useful data get transferred to cloud
storage (Rauniyar et al., 2016). Fog computing send
periodic data summary those are collected from various
cloud devices. For the IoT based education system enabling
fog computing technology is always more beneficial than
cloud computing technology (Saharan, K. P., & Kumar,
2015). Fog computing can include cloudlets at the network
edge and due to this it helps to create better and much
powerful data center. All the resource intensive IoT
systems are supported by the fog computing technology
(Hong et al., 2017). The operational differences occur
between cloud computing and fog computing because fog
computing is decentralized but cloud computing is not. Fog
computing technology works as an intermediate application
between hardware and software associated with remote
servers (Hussain, 2017).
Information that need to be transmitted to the university
server are regulated by fog computing (Wang et al., 2018).
Some of the issues of cloud computing gets resolved with
fog technology. All the related users would be able to
access the server much easily. It also gives immediate
response than any other technology (Giaretta, Dragoni &
Massacci, 2019). The chances of error occurrence
minimizes because in fog computing information are
segregated into small pieces and never send all together.
Issues of connection loss are resolved because it
holds multiple numbers of interconnected channels. It is
reviewed that fog computing gives higher security as in this
cases data are processed through multiple numbers of fog
nodes in complex distributive system (Amaxilatis et al.,
2017). Experiences of the users get improved a lot due to
real time and immediate response. Any query raised by
students will reach the teachers immediately and similarly
teachers will also be able to give immediate response on the
queries (Sarkar & Misra, 2016).
On the other hand Okafor (2017) argued that there are some
disadvantages also associated to fog computing technology.
Fog computing is a complicated system because it holds
additional layer of data processing and data storage. Due to
technical and operational excellence it holds additional
expense than cloud computing technology (Aljumah &
Ahanger, 2018). In order to operate the application easily
the universities should buy edge devices in terms of routers,
gateways, hubs etc. Fog computing has limited scalability;
therefore it is not scalable like cloud computing
technology. Fog computing can fulfill the demand of
increasing numbers of devices (Gul et al., 2017). The
bandwidth related and remote computer resource related
issues get resolved with fog computing.
Fog computing tends to offer better decision
making process and also ensures that all the relevant data
are managed within the cloud. Fog computing ensures that
the data are analyzed within the time so that it becomes
easy to manage the data within the cloud (Datta et al.,
2015). The fog computing performs their functions in
milliseconds and ensures that all necessary data are
evaluated within the system successfully. The article has
focused on evaluating the way fog computing works has
been discussed within the paper. Gateways are designed
with the aim of providing a better way of storing and
organizing the data (Hong et al., 2017). The key
components those are associated with the development of
fog architecture includes device, fog computing and cloud
for handling the complex data (Deshmukh & More, 2016).
This ensures that the speed, latency and variety are being
designed properly for managing the performance. The
paper has also focused on evaluating the roles that are
played by the fog nodes.
Frameworks and models for the fog computing in higher
education applications
Problem Technique
The preexisting technology
does not use edge computing
mechanism (Dolui & Datta
et al., 2017)
Use of new computing
paradigm for improving the
performance. The edge
mesh is considered as the
smartest computer

paradigm for managing the
centralized server.
Response rate is slower in
case of managing sensitive
data (Jayapandian, Pavithra
& Revathi, 2017)
Implementing two
algorithms: (1) integrating
fog for determining the
user’s data, (2) identifying
the shortest path for using
fog computing.
Prevention of DDOS attack Integrating handshaking
method for ensuring the
authentication process
effectively within the
system (Großmann, M.,
Ioannidis, 2019).
Challenges faced by
developers while accessing
IoT systems
Using API gateway for the
purpose of connecting the
micro services
Current system fails to
provide proper governance
Introduction of
computation framework for
managing the remote real
time monitoring.
Communication process gets
hampered and eventually
leads to impacting the
student’s data (Hosseinian-
Far, Ramachandran & Slack,
2017)
Using eWall monitoring
system
Improper monitoring and
governance of the activities
carried out within the higher
education (Dubey et al.,
2017)
Use of smart gateways in
the fog computing process
for enhancing the way
performance is monitored.
Problems faced while
decision making phase (Hu,
Dhelim, Ning & Qiu, 2017)
Implementing cloud to fog
architecture for securing
the edge of the network.
Education industry has the chances of
encountering a wide number of obstacles that gives rich
understanding towards the students. Fog computing has the
potential to enable the micro data facilities for the purpose
of providing modern on-site technologies (Elmroth et al.,
2017). This will also ensure that the latencies have
increased for the purpose of improving the individual
experience.
It has been observed that fog nodes are extremely
vibrant. Fog computing ensures that the users are capable
of managing the data with the use of different gadgets (Gia
et al., 2015). Both the computing technologies that are fog
computing and edge computing has the potential to provide
the functionalities in the terms of using analytic systems
that are located on the different sites of the system. Hence it
can be stated that with the help of proper technologies it
becomes effective to interact with the students using fog
computing (Giaretta et al., 2019).
V. Limitations
Fog computing is considered as the most
effective way of sharing and managing the data. This also
offers wide range of benefits. However apart from the
emerging benefits there are certain disadvantages that have
the potential to hamper the performance (Aljumah &
Ahanger, 2018). The wide range of limitations has the
potential to impact the performance of the facilities offered
at the higher education. Fog computing strategy has
inherited some issues from the cloud computing in terms of
security aspect. Privacy and security aspects are considered
as one of the main concern while using the fog computing
method (Khalil et al., 2019). The accuracy and adaptability
gets hampered due to full outsourcing of data. Beside the
wide range of benefits that are offered with the
combination fog and cloud computing there are certain
issues that hampers the performance. This issue tends to
arise due to architectural limitations (Khan et al, 2018).
Secondly, the broadcasting of every data shared within the
different layers of fog computing leads to data redundancy
and congestion among the data. This creates a major issue
while managing the storage and data effectively within the
system. Apart from this the fog computing technology also
lacks offering features such as cooperation and load
distribution (Kim, 2019). These features are not described
in the fog computing architecture and thus it becomes
difficult to manage the data within the different layers. The
main reason behind using edge computing is that it has the
potential to increase the network performance by
minimizing the latency rate. However it becomes very
difficult to handle multiple applications together at a time.
This hampers the way data are processes within the system
and also leads to increase in latency (Zhu et al., 2016).
After analyzing the architectural structure it can be stated
that there are possibilities of several issues that can hamper
the services that are offered with the use of the fog
computing.
Apart from this the major issues that are faced
with the use of fog computing is with security issues in the
wireless devices and the related privacy concerns (Song et
al., 2017). Secondly the authentication is considered as the
most concerned aspect in the fields of fog computing. Due
to huge number of involvement among the cloud providers
and service providers it becomes difficult to manage the
trust and also the flexibility gets complicated. This hampers
the overall performance and also can lead to launching
attacks for hampering the overall performance of the
system (Tsai et al., 2010). The security concern arises with
the use of fog computing due to number of devices that are
connected within the fog nodes. In this type of hacking the
IP addresses can be faked by the hackers for the purpose of
obtaining the information that are shared within the system.
Thus it can be stated that fog computing has the potential to
handle massive data that arises with the use of IoT on edge
of the network (Stoica et al., 2018). However the
drawbacks of using fog computing has the potential to
hamper the overall performance. Thus there is a need to
integrate proper structure for enhancing the performance.
VI. Discussion and open issues
The key objective of the paper was to identify the
researches that have been carried for the purpose of
understanding the role of fog computing in the field of
education IoT systems. In the process of developing the
taxonomy, the related articles with fog computing are

analyzed (Raman, 2019). The review focuses mainly on
reviewing the concepts that are associated with the fog
computing in higher education fields. The paper has also
evaluated the critical infrastructures that are used for
sharing the resources. Fog computing thus plays a crucial
role in managing the data and activities. This section is
responsible for determining the features that are offered
with the fog computing in the fields of education
applications. This section will include performance
evaluation, motivations, challenges and issues and future
directions on fog computing.
A. Performance evaluation
Performance evaluation is the technique that is
used for determining the various resource sharing
techniques that took place in fog computing of education
IoT systems. The paper has focused on evaluating the
resources that are needed for managing the resources
associated with the performance. This includes the factors
of providing low latency, decision making process, real
time processing and providing proper response time. This
also ensures that the feature such as energy consumption,
bandwidth maintenance and mobility also gets enhanced.
However it has been observed that there are several issues
that are faced while using the fog computing paradigm
(Zhang et al., 2018). Thus there is a need to engage the way
data are managed and protected within the network.
Firework paradigm is one of the new computing paradigms
that were proposed with the aim of facilitating better way
of data sharing. This paradigm ensures that the data sharing
facility is maintained with proper data privacy and integrity
for the stakeholders. Moreover the way data are handled
can be modified with the use of proper security processing.
The reason behind using an integrated and flexible
computing paradigm is to benefit the critical application
that takes place within the system (Zhamanov et al., 2017).
The critical applications that are performed by the higher
education system is preparing the mark sheet, managing the
admission process and hiring students.
The wide range of benefits that are offered with
the use of fog computing includes reducing the chances of
data transmission latency, reducing the end to end delay
and ensuring that quick response time (Yousefpour et al.,
2018). From the above analysis it can be stated that fog
computing has better features as compared to cloud
computing in the field of education application. This
ensures that the time is saved while accessing the data and
also the execution time can be reduced. The paper has
explained the importance of real-time governance that is
designed for the purpose of reducing the transmission
related issues. It is important for every member within the
system to maintain proper communication procedure for
ensuring better performance. The advanced services that
are likely to offered with the use of fog computing in the
higher education field is that it will secure the way data are
transferred and will also ensure that every communication
process are managed effectively. The focus of the
assessment us to reduce the latency and improving the
quality of service that is offered towards the student.
B. Motivation
Education sector has used several technologies
for the purpose of improving the performance. There is a
need to manage the resources effectively so that the
performance can be enhanced. In order to enhance the way
resources are managed within the education IoT system is
by using the three process that are computation offloading,
load balancing and the interoperability. The main reason
behind using fog computing in the fields of education is to
ensure that the major issues faced by the previous
architecture are being mitigated successfully (Yi et al.,
2015). For the purpose of providing better support towards
the system it is important to use proper architecture of the
fog computing. Thus it can be stated that in order to have a
better computing procedure it becomes essential to develop
a real time system that will be capable of managing the
performance.
C. Challenges and issues
Fog computing and edge computing has gained
huge importance in education sector. However it has been
observed due to huge amount of challenges it becomes
difficult to implement the computing process (Alrawais et
al., 2017). The shared resources feature has the potential to
impact the performance of fog computing. Apart from this
the other technical knowledge needs to be mitigated
properly for the purpose of improving the performance.
D. Recommendations
The recommendations are provided for the
purpose of managing the resources effectively. While
developing fog architecture it is important to focus the
latency and reliability of the system. The total time
consumed by the system can be reduced by re-planning the
development process. Moreover there is a need to develop a
real time response system that will be capable of providing
better support towards the education system.
VII. Learned lessons
In order to analyze the different components
related to the fog computing several research papers are
identified so that it becomes easy to gain the knowledge. It
can be stated that with the use of fog computing in the
fields of education system is that it helps in monitoring the
education related activities and also ensures that each data
are managed successfully within the system.
VIII. Conclusion
Thus from the above report it can be stated that
with the use of Fog computing it becomes easy to manage
the researches and the way IoT can be used in education
fields for the purpose of improving the performance. Fog
computing offers a better control over the privacy concept
so that it becomes easy to manage the data within the
system. With the use of fog computing it becomes easy to
increase the business productivity and the agility also gets
improved. Thus it can be stated that with the help of fog
computing it becomes easy to improve the productivity and
also the speed of the business performance gets enhanced.
The paper has focused on preparing an effective fog
computing technology for the education IoT system so that

it becomes easy to manage the services offered. In this
paper the major benefits and features of fog computing
implementation are determined. Along with this the key
issues that related to the fog computing are also determined
in the paper. In addition to this the paper has also provided
a methodical review for the purpose of depicting the
methods that are essential for analyzing the features related
to fog computing. Thus it can be concluded that with the
help of this research paper it will become easy to carry out
the future researches.
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