© 2018 IJRAR January 2019, Volume 6, Issue 1
www.ijrar.org (
E-ISSN 2348-1269, P- ISSN 2349-5138
)
IJRAR19J1651
International Journal of Research and Analytical Reviews (IJRAR)
www.ijrar.org
1386
A Comparison Analysis of Fog And Cloud
Computing
1
Gnaneswar Nair,
1
Hadresh G,
2
Pdinesh V
1,2
Lecturer, Information Technology Department,
1,2
R. C. Technical Institute, Ahmedabad, India
Abstract :
In recent years, Fog Computing is introduced as a powerful extension of cloud computing and services to the edge of
the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end users. The fog computing is
used to reduce the workload of the cloud computing by bringing basic computing services and analytic services to the edge of
network, providing computing resources closer to the end devices, mobility support, improving overall network efficiency and
performance and low latency. We explore the different applications of fog computing and various key comparison between cloud
computing and fog computing.
Index Terms
– Fog Computing, Cloud Computing, IOT.
I.
I
NTRODUCTION
Cloud computing has emerged and got popularity by increasing development of storage and processing technology, as well as
the success of the Internet, the cost-effectiveness of resource processing and availability. It has been increasingly adopted in many
areas including science and engineering not to mention business due to its inherent flexibility, scalability and cost effectiveness
[19]. Cloud computing is a very successful and effective technology, which is having many
advantages like efficiency, cost
effectiveness, easily accessible,
backup and recovery, software automation and quick deployment etc. But still there are
limitations like latency, security issues, issues related to internet connection due to increased ITO devices and smart devices now a
days. Fog computing is a promising solution to deal with the demands of the ever-increasing number
of Internet-connected
devices. The idea of fog computing is to extend the cloud to be closer to the things that produce and act on IoT data. Instead of
forcing all processing to back-end clouds, fog computing aims to process part of the services’
workload locally on fog nodes,
which are served as a near-end computing proxies between the front-end IoT devices and the back-end cloud servers. Putting
resources at the edge of the network only one or two hops from the data sources allows fog nodes
to perform low latency
processing while latency-tolerant and large-scale tasks can still be efficiently processed by the cloud [2]. In addition, the cost and
scale benefits of the cloud can help the fog to serve peak demands of IoT devices if the resources of fog nodes are not sufficient.
Also, many applications require the interplay and cooperation between the edge (fog) and the core (cloud), particularly for the IoT
and big data analysis [1]. From this point of view, fog computing is not aimed to replace cloud computing, but to complement it in
a new computing paradigm,
cloud-fog computing, which is to satisfy the increasingly sophisticated applications demanded by
users [2]. Fog computing gives the cloud a companion to handle the two hexa bytes of data generated daily from the Internet of
Things. Processing data closer to where it is produced and needed solves the challenges of exploding data volume, variety, and
velocity [3].
