Future of the Fog Domain: Solutions for Limitations and Better Technology

This research report delves into the future of the Fog Domain, exploring solutions for its limitations and providing a better technology for the future generation. It covers the comparison of cloud computing and fog computing, hidden channel attacks, data plane attacks, and control plane attacks.

FUTURE OF THE FOG DOMAIN

ABSTRACT – Fog computing refers to the paradigm of cloud computing where resources are placed close to the
network edges for dealing with the upcoming development or growth of any connected device. The smart city
applications like predictive maintenance as well as health monitoring eventually introduces a completely new collection
of the stringent requirements like lower latency. The extensive rise of the Smart Things has given rise to the
extraordinary increment in digital generated data. Several limitations are present in current cloud computing and these
limitations often become a major problem for the current technological world. The aim of this research report to find
solutions for all those limitations and providing a better technology for the future generation.
1. INTRODUCTION (15 MARKS)
The Internet of Things or IoT can be defined as the network
of home appliances, vehicles, physical devices or any other
item that is solely embedded with software, electronics,
sensors, connectivity and actuators that help to enable all the
objects in connection as well as exchange of data
(Stojmenovic & Wen, 2014). Each and every thing could be
uniquely recognized by the embedded computing system;
however has the capability of interoperation in the Internet
infrastructure that previously exists.
1.1. FOG COMPUTING
1.1.1. Background
Fog computing eventually refers to the decentralized
Internet architecture, which serves as the important and
significant extension of cloud computing and does its work by
the collaboration of at least one edge node device and thus
giving exact amount of management, localized control and
configuration (Bonomi et al., 2014). The main difference with
cloud computing is that in cloud computing the data is needed
to be accessed within the centralized mainframe. However, the
technology of fog computing enables the services that are
completely cloud based for expanding their limit of the
network edge of any specific device for offering local as well
as faster access to those particular edge devices. The network
of fog computing has two planes. They are the Control plane
and the data plane or forwarding plane. The Control plane is
responsible for providing the complete overview of the
network and thus it does its work with all the routing
protocols, running within the architectural control element
(Yorozu et al., 1987). The Data Plane on the other hand, helps
to determine the functions of all the data packets. It is
responsible for allowing the computing resources that are to
be placed in the network irrespective of its location.
1.1.2. Comparison of Cloud Computing and Fog
Computing
The most significant problem with the cloud computing is
that the user always has to be completely dependent on the
cloud repository as well as data access needs Internet
connectivity and allocation of bandwidth. This often becomes
a major problem for the user as they are being able to cope up
with these limitations (Bonomi et al., 2014). Moreover cloud
computing is extremely expensive and it becomes major
problem to afford this particular technology. Security is
another important problem in cloud computing. The data often
gets lost or hacked within the cloud. The best answer for this
type of problem is fog computing. The data could be easily
accessed within the devices locally, in spite of being
dependent on the repository of cloud. Fog computing would
be extremely helpful in boosting the accessibility, the
contextual usability and the easy usage of the device data
(Stojmenovic & Wen, 2014). The initiation of Fog Computing
substantially boosts the collaboration within data centers and
devices.
1.1.3. Standout of Fog Computing
The technological world has witnessed the most interesting
and extraordinary change in the digitally generated data from
all types of connected devices and Smart Things. The
exclusive rise of the applications and smart phones enable
data access and management of the real time end devices
(Clerk Maxwell, 1892). Fog computing helps to empower the
edge node devices for carrying out most of the local data
processing, and latency reduction for better Quality of Service
or QoS.
2. BACKGROUND/LITERATURE REVIEW (40 MARKS)
2.1. Cloud Domain
2.1.1. Hidden Channel Attack
Fang, Dejun and Guoliang, 2013, stated that cloud
computing is the most popular technology for the successful
delivery of any type of hosted services on the Internet
connectivity (Cui, Yu & Yan, 2016). It helps to enable any
organization in consuming the computing resources like
virtual machines or VM, applications and storages as a basic
utility. The most important and effective advantages of this
cloud computing mainly include elasticity, self service
provisioning, flexibility in migration, pay as per utilization
and workload resilience. There are four distinct models of
cloud computing (Yi, Qin & Li, 2015). They are private cloud,
public cloud, hybrid cloud and community cloud.
According to Cui, Richard and Qiao, 2016, cloud based
platforms of Internet of Things are hence the architecture are
utilized for connecting the virtual and real worlds (Sezer et al.,
2013). These types of platforms help all the organizations in
successfully managing the devices of Internet of Things in
terms of their connectivity or security and privacy. Moreover,
the collection of device data is done by these platforms. It
even ensures the interoperability of the Internet of Things for
building and running the applications. The data explosion of
the Internet of Things is also done with the help of these
specific platforms (Stojmenovic et al., 2016). The various

items are properly embedded with the software, electronics
and sensors.
Cloud domain provides various valuable applications
services in all types of application domains. These cloud
domains help to emerge within the market for leveraging
suitable IoT related services. There are various possibilities of
IoT clouds, however, no standard or comparative analysis is
been found within the literature database (Yarom & Benger,
2014). The most popular platforms of IoT cloud are involved
to solve various service domains like device management,
development of application, data management, and system
management to properly and significantly analyze, monitor,
visualize and research. This cloud domain is often vulnerable
to several attacks.
Yarom and Naomi, 2014 stated that in computer security,
hidden channel attack or side channel attack is the vulnerable
attack that is completely based on the data and information
obtained from implementing computer systems and not the
weaknesses in implementing the original algorithm (Yarom &
Benger, 2014). Software bugs and the cryptanalysis are the
algorithms. All the information regarding time, extra power
consumption, excess sound and the electromagnetic leaks are
solely responsible for this type of attacks as these information
are eventually exploited (Cui, Yu & Yan, 2016). Most of the
hidden channel attacks need technical knowledge for the
internal operation of this system. The effective black box
attacks are extremely effective in this phenomenon and hence
the differential analysis of power is done. The rise of the
advanced Web 2.0 applications as well as SaaS or software as
a service have eventually raised the probability of the hidden
channel attacks over the web (Yi, Qin & Li, 2015). This can
also occur when the transmissions are encrypted between the
server and the web browser.
Figure 1: Hidden Channel Attacks
The above figure provides a clear image of the process of
hidden channel attacks. There are distinctly two keys. One is
the real key and the other one is the fake key. Any one of the
key enters into the system as the input and finally goes to the
application window or hidden window.
Figure 2: Hidden Channel Attacks on Smart Cards
The above figure describes about the hidden channel
attacks on smart cards. The secret key generates a cipher
algorithm and hence the hidden channel attacks occur
eventually.
2.1.2 Data Plane Attack
Wortmann and Flüchter, 2015 stated that Internet of Things
is a specific concept of computing, which eventually describes
about the idea of various physical objects that are connected
or linked to the connectivity of Internet and thus have the
ability in identification of all other devices (Luan et al., 2015).
Fog computing is the next advancement after cloud computing
and Internet of Things. It is the perfect amalgamation of both
cloud computing and Internet of Things.
Sezer et al. 2013 stated that, fog computing eventually
comprises of control plane and data plane. Both of these
control plane and data plane are prone to various attacks.
These attacks are excessively dangerous for the fog computing
(Yi, Li & Li, 2015). The data plane is also called the
forwarding plane. It is responsible for forwarding the traffic to
the subsequent hop following the path of the desired location
network as per the logic of control plane. The packets of data
plane eventually go via the router present. All the routers or
switches utilize what any control plane is built of disposing
the outgoing as well as incoming packets and frames (Sarkar,
Chatterjee & Misra, 2015). The best example of data plane is
to move the data packets on the transit path.
As per Kreutz, Fernando and Paulo, 2013, there are
various attacks in this data plane. The new emerging attacks
on network target the data plane of fog computing (Fang,
Yang & Xue, 2013). These types of attacks were majorly on
the hardware, however, recently these attacks have moved to
the routers of data plane. The major problem occurs while
forwarding the packets. There are various software
vulnerabilities in the processing devices and they are
extremely threatened to attacks. The data plane of fog
computing is solely exploited by several vulnerabilities within
the software of packet processing for the purpose of launching
any dangerous denial of service attack in the infrastructure of
network (Yi et al., 2015). The denial of service attack utilizes
any particular data packet for consuming the complete link
bandwidth of outgoing link of the router. There are network

based defences for detecting such situations and stopping or
preventing any type of malicious activity within the network
processor. With the help of hardware monitor, this type of
problem is detected and the recovery system is used for
restoring the processor of the network. This eventually allows
being in a safe state and having six cycles (Dastjerdi & Buyya,
2016). The higher speed detection as well as recovery system
ensures that the network processors are protected efficiently
and effectively from the attacks of denial of service on the
data plane of fog computing.
2.1.3. Control Plane Attack
According to Gubbi et al., 2014, the next generation of
cloud computing is Internet of Things. Most of the objects that
are surrounded are on the network in any form. The
technologies of RDIF or Radio Frequency Identification or the
sensor network help in meeting the problems that are
embedded within the systems of information and
communication technology (Wortmann & Flüchter, 2015).
This eventually results in generating huge data amount that
are being stored, presented or processed in an extremely
effective and efficient manner. IoT substantially comprises of
services, which could be delivered in traditional manner.
Fogging is the decentralized infrastructure of computing
where the data and applications are evenly distributed within
the most effective and efficient location within the cloud and
data source (Yi, Qin & Li, 2015). This type of technology is
mainly utilized for improvising or increasing the effectiveness
and the efficiency; however this technology can also be
utilized for various reasons of compliance and security or
privacy (Sezer et al., 2013). The most popular and effective
applications of fog computing mainly include smart buildings,
smart city, software defined networks, vehicle networks and
smart grids. Fog computing mainly focuses on the network
edge.
The second part of the fog computing after data plane is the
control plane. This control plane helps in taking the important
decisions regarding the destination of traffic (Stojmenovic,
2014). The packets of control plane are eventually set to or
even created by itself the router. This control plane even
comprises of functions like configuration of the system,
overall management and even the exchanging of information
of the routing table. The controller of router exchanges the
information of topology with all other routers, thus
constructing the typical routing table on the basis of routing
protocol like BGP, OSPF and RIP (Mukherjee et al., 2017).
The packets of control plane are eventually processed for
updating the information of routing table with the help of
router and control plane is also known as the network
signalling. As the functions of control plane are not always
performed on every arrival of individual packet, there is not
strict constraint of speed and moreover, it is extremely cost
and time effective (Aazam & Huh, 2014). The best example of
control plane is not knowing any specific route of a bus.
As per Shin and Guofei, 2013, the control plane of the fog
computing is also affected with several vulnerable attacks or
threats. The most vulnerable amongst all these attacks is the
CXPST or e Coordinated Cross Plane Session Termination.
This is a particular type of distributed denial of services or
DDoS attacks (Madsen et al., 2013). The attacking procedure
of this threat is by extending the previous work, demonstrating
vulnerabilities in the routers, which enables the adversary in
disconnecting the pair of routers by simply utilizing the data
plane traffic (Luan et al., 2015). With the help of updates of
BGP, selecting the sessions of BGP, there are various threats
of CXPST. The series of updates substantially surpasses all
the computational capacity of any affected router, hence
crippling the ability for making the decisions of routing. This
particular type of vulnerability is responsible for exploiting
the global scope of the updates of BGP. This type of attack
induces the instability of the Internet as a whole (Truong et
al., 2015). CXPST even computes the centrality measures of
the topology of network involved and hence the information is
used for properly selecting any collection of the sessions of
BGP. This even helps in disrupting the network by utilizing
the attack of ZMW.
The BGP stability or the performance of network is done in
the control plane of fog computing (Shin & Gu, 2013). When
there is a change in networks, the routes, which are not
needed, are required to be withdrawn effectively. The
functionality of control plane is to restore the network when
the affected routers make the message processing completed
and accurate. For the purpose of creating instability on the
control plane of fog computing, the attacker eventually applies
the attacks of ZMW and also uses the data traffic for tricking
the pair of routers to disconnect from one another (Yarom &
Benger, 2014). There are lot of problems like withdrawal of
route, advertisements and recalculations. The disruption in the
control plane is solely generated but is not restricted to any
one set. As the targeted link of the network is not utilized by
the routers after the failure of the BGP session, there is no
utilization of the link by the traffic (Vaquero & Rodero-
Merino, 2014). This phenomenon eventually enables the two
routers for communicating amongst each other; there will be
no congestion in the network traffic. The routers that are
targeted after sometimes, again establishes the session of
BGP. The bot traffic shifts to the link that is targeted like all
the previous routes and thus the attack is again resumed
without any problem from the attacker (Yi, Qin & Li, 2015).
Thus, the targeted session of BGP is destroyed and the cycle
repeats itself. The routers are solely affected in this sector and
CXPST is responsible for inducing the flapping of targeted
route. These types of attacks are extremely common in the
control plane of fog computing.
2.2 Fog Domain
2.2.1. Authentication and Trust Issues
The proper extension of cloud computing for the edge of
any network is known as fog computing (Yi, et al., 2015). The
other name of this technology is fogging or edge computing
that helps to facilitate various operations for services of
networking within the end devices and data centers of cloud
computing. It is the most advanced method of bringing the
technology or capabilities of cloud computing to the network
edge and hence as a result, it is rapidly growing for the
consumption of services of cloud and generation of huge

amount of data (Gubbi et al., 2013). For the successful
handling all these problems in fog computing, these services
take up the technology of Internet of Things or IoT at the
exclusive edge of network for executing the processes
perfectly and without any type of problems. The platform for
fog computing or edge computing with the Internet of Things
is extremely popular and acceptable by all users (Mukherjee et
al., 2017). The domain where fog computing is being operated
is known as the fog domain of that platform. It is utilized by
all users of fog computing. Various applications like routers,
IP video cameras and switched are utilized in this
phenomenon.
Yi, Cheng and Qun Li 2015, stated that, in spite of having
all these exclusive and extra ordinary benefits, there are some
of the most threatening and dangerous issues in implementing
fog computing or using fog domain (Fang, Yang & Xue,
2013). The first and the most significant issue in the fog
domain is the authentication issues or trust issues. The trust
issues of this particular technology are challenged and users
do not wish to use this system (Kreutz, Ramos & Verissimo,
2013). The major characteristics of the fog domain include
lower latency, location awareness, supporting geographic
distribution and mobility in end services. Moreover, the fog
domain has the sole capacity to process the highest number of
nodes and a wireless access (Aazam & Huh, 2014). The real
time applications and the heterogeneity features of the fog
domain make this fog domain extremely popular and effective
for all.
Figure 3: Three Tier Architecture of Fog Computing
The above figure provides a clear demonstration of the
three tier architecture of fog computing and all the three tiers
have different uses. The first tier is the Things or End
Devices, the second tier is the fog and the final tier is the
cloud (Dastjerdi & Buyya, 2016). The fog cloud interface is
supposed to provide various end to end services that involve
the distribution of cloud services in fog and the proper
collaboration of cloud services in storage of data and
computing tasks.
According to Vaquero, Luis and Luis 2014, the trust issues
in fog domain mainly address the trust of any fog service. This
fog domain ensures the trust level by the fog services and the
well established trust models within cloud computing could be
eventually applied to the fog services for the lack of
centralized management and various mobility issues
(Wortmann & Flüchter, 2015). Although, the provider of fog
services provides various attributes for the proper
measurement of trust in any service and simultaneously
verifies and monitors the attributes. Amongst the various
models of trust management in cloud computing, the trust
model that is based on reputation is broadly utilized within the
services of e commerce (Peng et al., 2016). Most of the time,
the reputation of any particular service provider is extremely
useful for choosing within the various service providers. The
proper verification of SLA or Service Level Agreement is
solely required in the trust issues of fog domain. This
verification is done by the third party and they even monitor
the fog domain. The networks of Internet of Things are
supposed to provide absolutely secured and reliable services
to its users (Yi, Li & Li, 2015). All the devices, which are the
sole part of the fog networks, have a specific trust level on
each other. Authentication is the next important and
significant feature in the establishment of set of relations
within the fog nodes and the devices of Internet of Things.
This entire phenomenon occurs within the network. However,
this is not sufficient or adequate since the devices always
malfunctions and becomes suspicious to the malicious attacks
(Stojmenovic, 2014). Trust, on the other hand, fosters the
relations that are solely based on the previous actions. Trust is
responsible for playing a two way role within the fog network
and these fog nodes offer major services to the devices of IoT
for sending data or any other valuable processing requests to
verify all the intended fog nodes (Cui, Yu & Yan, 2016).
Reliability as well as security are maintained with this fog
network and there are unique challenges faced in the
environment of fog computing.
According to Mukherjee et al., 2017, authentication issues
in the fog domain refer to the most significant requirement of
fog network. For the successful access of the services of any
fog network, the particular device should at first become the
part of network through proper authentication within the fog
network (Stojmenovic et al., 2016). This specific requirement
is extremely essential and important for the perfect detection
and prevention of the entrance of unauthorized nodes. This
becomes the most important challenge since all the devices
that are being involved within the network are properly
constrained in several methods with storage, power and
processing (Vaquero & Rodero-Merino, 2014). The traditional
mechanism of authentication with the help of PKI or public
key infrastructure and certificates are not appropriate for the
reason of various resource constraints of the devices of

Internet of Things. Each and every authentication protocols
are based on the public key infrastructure by utilizing the
multicast authentication to securely communicate within the
network (Kreutz, Ramos & Verissimo, 2013). Authentication,
like processing services and storage, also require to be
perfectly authenticated for the fog node with intermediary.
The operations model can prevent or detect the unauthorized
nodes from being the part of fog network. The fog nodes even
limit the service requests from any type of malicious or
compromised nodes. The most significant authentication issue
in fog domain is the dynamic fog nodes (Luan et al., 2015).
These frequently join and even leave the layer of fog and it
needed for ensuring the uninterrupted services for the
registered end users, the moment any new node of fog joins
and leaves. There is a major complexity in the phases of re
authentication and registration without major overhead.
3. ISSUES/ SOLUTIONS (10 MARKS)
3.1. Network Security in Fog Computing
Wireless networking has taken the entire technological
world. The users are being benefitted from this (Firdhous,
Ghazali & Hassan, 2014). For the excess and dominance of
this wireless within fog networking, the network security is an
extremely important and significant concern for the fog
networking. The most significant attacks of this network
security mainly include the sniffer attacks and jamming
attacks (Roman, Lopez & Mambo, 2018). These specific types
of attacks are solely addressed within the domain of wireless
networking and the configurations are being manually
generated by any typical administrator of network. This helps
to isolate the traffic of network management from the regular
traffic of data (Saharan & Kumar, 2015). However, the
various fog nodes are eventually deployed on the Internet
edge, thus bringing huge burden on the network management.
The expenses of the maintenance of all these massive or huge
scale servers of cloud that are spread in the total network
edge. This spreading is done without any type of access in
maintenance (Hou et al., 2016). These types of problems
could be extremely dangerous for the fog computing and the
users, who are utilizing this technology.
3.1.1. Solution to Network Security Issue
However, this type of issue could be solved with the help
of SDN or software defined networking (Perera et al., 2017).
It is the specific term that encompasses the various types of
network technology targeted in making any network flexible
or agile like the storage infrastructure or virtualized server in
the data centre (Bellavista & Zanni, 2017). This particular
type of networking can easily solve the problem of wireless
network security in fog computing. The network scalability
would be resolved. The network monitoring and the IDS or
Intrusion Detection System are incorporated within the system
(Zeng et al., 2016). This helps to monitor the applications and
make route for traffic. The traffic isolation and the
prioritization are the second method of helping fog network
security. This is utilized for preventing any type of attack
from the congestion of network or even any type of dominated
shared resources like disk input output and CPU (Samie,
Bauer & Henkel, 2016). SDN has the capacity to utilize
VLAN ID/tag for isolating the traffic within the VLAN group
and thus successfully segregating the malicious traffic. The
third method is the access control of network resources
(Cirani et al., 2015). Here, the SDN controller helps to control
the access of the network. The fourth method is the network
sharing. The router that is enhanced of fog within the network
is shifted to cloud for establishing the identity.
Figure 4: Environment of Fog Computing
3.2. Secure Data Storage
The next important issue within fog computing occurs
when the user data is eventually outsourced and the total
control over the data should be handed over to the fog node,
thus introducing similar security threats like in cloud
computing (Shankarwar & Pawar, 2015). In the beginning, it
is extremely difficult in ensuring the integrity of the data as
the data that is outsourced has the tendency to be lost or
inaccurately modified. The next problem is that the data that is
uploaded could be easily abused or hacked by the
unauthorized or unsanctioned users with wrong intentions
(Alsaffar et al., 2016). This type of problem is extremely
vulnerable as the hacker or the attacker changes the content of
the data or information and the receiver gets the modified
data.
3.2.1 Solution to Secure Data Storage Issue
For the purpose to solve this specific type of problem of
data integrity in fog computing (Cao et al., 2015). To address
these types of threats, the service of auditable storage of data
is present for protecting the data just like cloud computing.
There are various techniques and tools like searchable
encryption as well as homo morphic encryption are
amalgamated for providing confidentiality, integrity or even
verifiability for the system of cloud storage (Yaseen et al.,

2016). This would substantially enable the client in checking
whether the data is secured from the unauthorized servers.
There is a public auditing for the purpose of storing data
within cloud that is reliable on TPA or third party auditor
(Hassan et al., 2015). This is done by technique of random
mask and homo morphic authenticator for protecting privacy
and security against this TPA. For ensuring the reliability of
data storage, the systems or prior storage utilize the network
coding. This increases the detection of data corruption and
data repairing (Bittencourt et al., 2015). The low latency is
properly achieved with this technique in fog computing.
3.3. Secure and Private Data Computation
The third significant issue or challenge in fog computing is
the achievement of privacy preserving and security preserving
computation outsourcing to the respective fog nodes (Stergiou
et al., 2018). The first method is the verifiable computing. It is
responsible for enabling the computing device for simply
offloading the computation of any specific function to the
others like the authorized servers for maintaining the
verifiable results. All the other servers then eventually
evaluate that function and finally returning the outcome with a
valid proof that computation of that function was accurately
carried out (Nandyala & Kim, 2016). Within fog computing,
for the purpose of instilling confidence in computation
offloaded to the respective fog node, the authorized user of the
fog should have the ability to determine the computation
accuracy.
3.3.1. Solution to Secure and Private Data Computation Issue
There are few methods to complete verifiable computing.
It enables the server in returning a non interactive proof for
verification of the client (Beri & Behal, 2015). It is a type of
protocol and this protocol would provide privacy for both
input and output so that server does not have any idea of the
input or output. This is also done without any type of extra
cost or expenses. Pinocchio is a popular system that helps the
client in verifying the general computations to rely on the
assumptions of cryptography (Yannuzzi et al., 2017).
Moreover, the client even creates an evaluation key for
describing the computation with Pinocchio, hence producing a
valid proof of accuracy. Thus, the problem is easily solved.
The second method here is data search. The privacy of the
confidential and sensitive data is protected from the end users;
the process of encryption is being used (Patil, 2015). The
encryption is done before the data is being outsourced to the
fog node, thus making the utilization of data services
extremely effective. The most important and significant
service here is the keyword search, which means the search of
keyword within the data files that are encrypted. There are
various encryption schemes, which allow any user in
searching the encrypted data securely without decryption
(Firdhous, Ghazali & Hassan, 2014). This particular method
would reduce the chance of data loss by incrementing
encryption, isolation of query and support to the hidden query.
Figure 5: Computation Domain of Cloud, Fog, Edge,
Mobile Cloud and Mobile Edge Computing
4. FUTURE RESEARCH (5 MARKS)
4.1. Gap Analysis and Various Future Directions
Fog computing is the newest advancement in the field of
technology and cloud computing (Roman, Lopez & Mambo,
2018). This fog computing completely resides within the close
proximity of various end users and thus extends the facilities
of cloud based. For serving the widely distributed sensors and
end devices, fog computing plays the significant role. Hence,
in the current years, this technology of fog computing is
becoming one of the most significant research fields from
business perspectives as well as academics (Saharan &
Kumar, 2015). The future directions of fog computing are
given below.
4.1.1. Context Aware Resource or Service Provisioning
The context awareness eventually leads to effective service
and resource provisioning within fog computing (Bellavista &
Zanni, 2017). There are various examples from where the
contextual information could be received. The best examples
of information form mainly include environmental context,
application context, user context, network context and device
context. In spite of having various contextual information
within fog computing, this particular research comprises of
various features or aspects of this contextual information for
managing the resources and services (Samie, Bauer & Henkel,
2016). This could be the potential field in the fog based work
in future.
4.1.2. Sustainable as well as Reliable Fog Computing
This is the second future scope of fog computing. The
sustainability within the technology of fog computing solely
optimizes all the environmental and economic influence to a
greater extent (Shankarwar & Pawar, 2015). The complete
architecture of sustainability of fog computing provides
assurance to the quality of service, reusability of services and

efficiency to energy. Moreover, the sector of reliability will
also be maintained while making the fog nodes consistent.
Thus, the fault tolerance would be increased and performance
would be higher (Patil, 2015). It is expected that in the near
future, these features would be available for fog computing.
4.1.3. Distributed Deployment of Application
The fog nodes are solely and substantially distributed over
the network edge and that all of them are not occupied with
good resources. In this particular scenario, the deployment of
large scale applications on the single fog node is not at all
feasible (Beri & Behal, 2015). The modular growth and
development of the applications is the best solution to the fog
nodes. In future, there is a high chance that the problems like
management of latency and assurance of Quality of Service.
5. ADVANTAGES/ DISADVANTAGES (5 MARKS)
5.1. Advantages of Fog Computing
Internet of Things can be closely recognized with the
RFID since the mode of communication includes wireless
technologies, sensor technologies and even QR codes (Cao et
al., 2015). This Internet of Things is properly significant as
any object that has the ability to represent itself in digital
means is greater than the original object (Sezer et al., 2013).
The objects not only refer to the systems, tablets, computers or
smart phones. This technology solely describes to all the
objects that are communicated or connected in any intelligent
manner. The physical world can become the largest
information system with the help of Internet of Things. The
application fields for the technologies of IoT are numerous
and diverse in nature (Yannuzzi et al., 2014).
Fog computing is the next stage of Internet of Things.
There are various significant advantages if this particular
technology (Yannuzzi et al., 2017). The main advantages of
fog computing help to understand the importance as well as
the significance of fog computing. The first and the foremost
advantage of this fog computing is that this specific type of
technology could be solely identified or distinguished form
the cloud by the help of its proximity to the respective end
users (Aazam & Huh, 2014). The second significant
advantage of this fog computing is that it provides
decentralized computing. This eventually means that the
technology of fog computing is responsible for providing
dense geographical distribution and the best support. This
particular advantage of fog computing makes the technology
extremely popular and well accepted by all users. The third
important advantage of fog computing is that it helps to
provide lower latency to the users (Bonomi et al., 2014). Due
to the lower latency, the application could be easily utilized by
all the users. Moreover, it helps to provide awareness of
location from where the application is being utilized and thus
the quality of all the services are improvised or improved. Due
to this constant up grading applications, the service quality
could be easily improved without any type of complexity. The
next important advantage of fog computing technology is that
it is extremely cost effective and thus does not incur huge
costs (Clerk Maxwell, 1892). The final advantage of this fog
computing is that it helps to gain real time applications.
5.2. Disadvantages of Fog Computing
The technology of fog computing helps in extending the
cloud computing as well as services to the network edge thus
bringing all the cloud benefits and cloud power where data is
kept or stored (Mukherjee et al., 2017). The most significant
goal of this fogging or fog computing is to improve and
increase the efficiency and thus reducing the data amount that
is to be transported to the specific cloud for the purpose of
storage, analysis and processing (Cui, Yu & Yan, 2016).
There are various disadvantages of fog computing as well.
The most important disadvantage or demerit of fog computing
is that there is no security and privacy (Saharan & Kumar,
2015). The technology is vulnerable to all types of security
threats and risks and thus is often avoided by several users.
The next important disadvantage of this fog computing is that
the data volume is extremely low. If huge amount of data
would be utilized in this application, there is a higher chance
that this data would lose integrity (Roman, Lopez & Mambo,
2018). Moreover, those systems, which are explicitly larger
and take up only restricted data amounts, do not gain any
advantage when fog computing is being implemented. The
other disadvantages of the fog computing mainly include the
lack of collaboration and lower latency. Due to this slower
latency and lack of collaboration, it is extremely difficult to
implement the technology (Luan et al., 2015). These
disadvantages of fog computing make the technology,
sometimes, extremely difficult to implement.
6. CONCLUSION (5 MARKS)
Therefore, from the research report on Future of the Fog
Domain, conclusion can be drawn that fog computing is the
typical promising part of IT or information technology, which
helps to extend the cloud computing the network edges. This
is also called the fog networking and this is the basic type of
decentralized computing infrastructure, where all the
computing resources or application services are evenly
distributed within any efficient, effective and logical location,
irrespective of the time. This also comprises of the source of
data to the respective cloud. The significant goal or objective
of this fog computing is the improvement of efficiency and
hence successfully reducing the data amount, which are
required to be transported or shifted to that cloud for the
purposes of analysis, storage, manipulation and processing.
Although, this specific technology of fog computing is always
used for the reason of efficiency, this is even utilized for
various reasons like compliance as well as security and
privacy. There are various objectives of fog computing like
latency management, cost management, network management,
computation management, applications management, data
management, power management and many others. These are
referred to the service level objectives. The users, who opt for
fog computing in their business, have all these service level
objectives within their business. This research report has
solely discussed about the various features of fog computing
by providing a brief literature review. This literature review
has discussed about the main topic by taking into
consideration of various renowned authors and researchers.

The next part of the report discusses about the various security
issues with their probable solutions. The report has also given
a clear view of the advantages and disadvantage and
directions for future in fog computing. Hence fog computing
is one of the most important and significant technology.
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