BANSILAL RAMNATH AGARWAL CHARITABLE TRUST`S
VISHWAKARMA INSTITUTE OF TECHNOLOGY
PUNE- 411 037
(An Autonomous Institute Affiliated to University of Pune)
A
Seminar
on
“FOG computing”
Submitted By
Apoorva Ajay Ambesange
Under The Guidance of
PROF. Amol Bhilare
Department of Computer Engineering
2015-16
BANSILAL RAMNATH AGARWAL CHARITABLE TRUST`S
1
VISHWAKARMA INSTITUTE OF TECHNOLOGY
PUNE-411 037
(An Autonomous Institute Affiliated to University of Pune.)
CERTIFICATE
This is to certify that the Seminar titled “FOG computing” has been completed in the
academic year 2015 – 2016, by Apoorva Ambesange in partial fulfillment of
Bachelors Degree in Computer Engineering as prescribed by University of Pune.
PROF. Amol Bhilare
PROF. S. B. Karthick
(Guide)
(H.O.D. of Computer Dept.)
Vishwakarma institute of technology
Vishwakarma institute of technology
Pune
Pune
Place: Pune
Date: 26/09/2015
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ACKNOWLEDGEMENT
I would like to express my deep and sincere gratitude to my guide,
Prof. Amol Bhilare , for his unflagging support and continuous encouragement
throughout the seminar work. Without his guidance and persistent help this report
would not have been possible
I would like to take this opportunity to thank Head Of Department ,
Computer for providing us with a highly conductive studying and working
environment for this seminar.
Apoorva Ambesange
Pune
26/9/2015
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INDEX
Chapter Title
Page No.
Abstract
1. Introduction
06
2. Cloud computing
07
2.1 Introduction
2.2 Disadvantages of cloud computing
3. FOG computing
3.1 Introduction
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3.2 Characterstics of FOG computing
3.3 Why do we need FOG computing
4. What we can do with FOG
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5. Security in FOG
12
Conclusion and Future scope
15
References
16
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ABSTRACT
Fog computing is not a replacement of cloud it is just extends the cloud computing
by providing security in the cloud environment. Similar to Cloud, Fog provides data,
compute, storage, and application services to end-users.
Cloud computing promises to significantly change the way of use computers and
store our personal and business information .With these new computing and
communication paradigms arise new data security challenges . Existing data
protection mechanisms such as Encryption have failed to protect the data in the
cloud from unauthorized access.
We proposed a different approach for securing data in the cloud using offensive
decoy technology. We monitor data access in the cloud and detect abnormal data
access patterns.When unauthorized access is suspected and then verified using
challenge questions, we launch a disinformation attack by returning large amounts of
decoy information to the attacker. This protects against the misuse of the user’s real
data. Experiments conducted in a local file setting provide evidence that this approach
may provide unprecedented levels of user data security in a Cloud environment.
Also I’m going to elaborate the motivation and advantages of Fog computing, and
analyze its applications in a series of real scenarios, such as smart traffic lights in
vehicular networks and software defined networks
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Chapter 1
INTRODUCTION
CISCO recently delivered the vision of fog computing to enable applications on
billions of connected devices, already connected in the Internet of Things (IoT), to run
directly at the network edge. Customers can develop, manage and run software
applications on Cisco IOx framework of networked devices, including hardened
routers, switches and IP video cameras. Cisco IOx brings the open source Linux and
Cisco IOS network operating system together in a single networked device (initially
in routers). The open application environment encourages more developers to bring
their own applications and connectivity interfaces at the edge of the network.
Cloud computing has become the buzz word during the recent years.
But it largely depends on servers which are available in a remote location, resulting in
slow response time and also scalability issues. Response time and scalability plays a
crucial role in machine to machine communication and services. The edge computing
platform solves the problems by the simple idea of locating small servers called edges
servers in the vicinity of the users and devices and passing to the servers some of the
load of center servers and/or user’s devices.
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Chapter 2
WHAT IS CLOUD COMPUTNG?
2.1. CLOUD COMPUTNG
Cloud computing is a delivery platform which promises a new way of accessing and
storing personal as well as business information. Cloud computing refers to the
practice of transitioning computer services such as computation or data storage to
multiple redundant offsite locations available on the Internet, which
allows application software to be operated using internet-enabled devices.
In Existing data protection mechanisms such as encryption was failed in securing the
data from the attacker. It does not verify whether the user was authorized or not.
Cloud computing security does not focus on ways of secure the data from
unauthorized access.
In 2009 we have our own confidential documents in the cloud. This file does not have
much security. so, hacker gains access the documents. Twitter incident is one example
of a data theft attack in the Cloud.
2.2. Disadvantages
 No body is identified when the attack is happen.
 It is complex to detect which user is attack.
 We can not detect which file was hacking.
 Cloud Computing Issue: Bandwidth
Transmitting and processing data requires bandwidth . The more data, the
more bandwidth is needed. Current cloud computing models can’t keep up with the
amount of bandwidth that will be needed.
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Chapter 3
WHAT IS FOG COMPUTING?
3.1. FOG COMPUTING
Fog computing is a model in which data, processing and applications
are concentrated in devices at the network edge rather than existing almost entirely in
the cloud.Fog Computing is a paradigm that extends Cloud Computing and services to
the edge of the network, similar to Cloud, Fog provides data, compute, storage, and
application services to end-users.
Fog computing is a paradigm which extends cloud computing
paradigm to the edge of the network. Terms Edge Computing and Fog
Computing are often used interchangeably. Similar to Cloud, Fog provides data,
compute, storage, and application services to end-users. This enables new breed of
applications and services.
3.2. CHARACTERISTICS OF FOG COMPUTING :



Proximity to end-users, its
Dense geographical distribution
Support for mobility.
Fog reduces service latency, and improves QoS (Quality of
Service), resulting in superior user-experience. Fog Computing supports emerging
Internet of Everything (IoE) applications that demand real-time/predictable latency
(industrial automation, transportation, networks of sensors and actuators). Fog
paradigm is well positioned for real time Big Data and real time analytics, it supports
densely distributed data collection points, hence adding a fourth axis to the often
mentioned Big Data dimensions (volume, variety, and velocity).
Unlike traditional data centers, Fog devices are geographically
distributed over heterogeneous platforms, spanning multiple management domains.
That means data can be processed locally in smart devices rather than being sent to
the cloud for processing.
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3.3. WHY DO WE NEED FOG COMPUTING?
In the past few years, Cloud computing has provided many opportunities for
enterprises by offering their customers a range of computing services. Current “payas-you-go” Cloud computing model becomes an efficient alternative to owning and
managing private data centers for customers facing Web applications and batch
processing Cloud computing frees the enterprises and their end users from the
specification of many details, such as storage resources, computation limitation and
network communication cost.
However, this bliss becomes a problem for latency-sensitive
applications, which require nodes in the vicinity to meet their delay requirements.
When techniques and devices of IoT are getting more involved in people’s life,
current Cloud computing paradigm can hardly satisfy their requirements of mobility
support, location awareness and low latency.
Fog computing is proposed to address the above problem. As Fog
computing is implemented at the edge of the network, it provides low latency,
location awareness, and improves quality-of-services (QoS) for streaming and real
time applications. Typical examples include industrial automation, transportation, and
networks of sensors and actuators. Moreover, this new infrastructure supports
heterogeneity as Fog devices include end-user devices, access points, edge routers and
switches. The Fog paradigm is well positioned for real time big data analytics,
supports densely distributed data collection points, and provides advantages in
entertainment, advertising, personal computing and other applications
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Chapter 4
4. WHAT CAN WE DO WITH FOG?
We elaborate on the role of Fog computing in the following
motivating scenarios. The advantages of Fog computing satisfy the requirements of
applications in these scenarios.
Smart Traffic Lights and Connected Vehicles:
Video camera that senses an ambulance flashing lights can
automatically change street lights to open lanes for the vehicle to pass through traffic.
Smart street lights interact locally with sensors and detect presence of pedestrian and
bikers, and measure the distance and speed of approaching vehicles. Intelligent
lighting turns on once a sensor identifies movement and switches off as traffic passes.
Neighboring smart lights serving as Fog devices coordinate to create green traffic
wave and send warning signals to approaching vehicles. Wireless access points like
Wi-Fi, 3G, road-side units and smart traffic lights are deployed along the roads.
Vehicles-to Vehicle, vehicle to access points, and access points to access points
interactions enrich the application of this scenario.
Wireless Sensor and Actuator Networks:
Traditional wireless sensor networks fall short in applications
that go beyond sensing and tracking, but require actuators to exert physical actions
like opening, closing or even carrying sensors. In this scenario, actuators serving as
Fog devices can control the measurement process itself, the stability and the
oscillatory behaviours by creating a closed-loop system. For example, in the scenario
of self-maintaining trains, sensor monitoring on a train’s ball-bearing can detect heat
levels, allowing applications to send an automatic alert to the train operator to stop the
train at next station for emergency maintenance and avoid potential derailment. In
lifesaving air vents scenario, sensors on vents monitor air conditions flowing in and
out of mines and automatically change air-flow if conditions become dangerous to
miners
IoT and Cyber-physical systems (CPSs):
Fog computing based systems are becoming an important class of
IoT and CPSs. Based on the traditional information carriers including Internet and
telecommunication network, IoT is a network that can interconnect ordinary physical
objects with identified address. CPSs feature a tight combination of the system’s
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computational and physical elements. CPSs also coordinate the integration of
computer and information centric physical and engineered systems.
IoT and CPSs promise to transform our world with new relationships
between computer-based control and communication systems, engineered systems
and physical reality. Fog computing in this scenario is built on the concepts of
embedded systems in which software programs and computers are embedded in
devices for reasons other than computation alone. Examples of the devices include
toys, cars, medical devices and machinery. The goal is to integrate the abstractions
and precision of software and networking with the dynamics, uncertainty and noise in
the physical environment. Using the emerging knowledge, principles and methods of
CPSs, we will be able to develop new generations of intelligent medical devices and
systems, ‘smart’ highways, buildings, factories, agricultural and robotic systems.
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Chapter 5
SECURITY IN FOG COMPUTING:
There are various ways to use cloud services to save or store files,
documents and media in remote services that can be accessed whenever user connect
to the Internet. The main problem in cloud is to maintain security for user’s data in
way that guarantees only authenticated users and no one else gain access to that data.
The issue of providing security to confidential information is core security problem,
that it does not provide level of assurance most people desire. There are various
methods to secure remote data in cloud using standard access control and encryption
methods.
It is good to say that all the standard approaches used for providing
security have been demonstrated to fail from time to time for a variety of reasons,
including faulty implementations, buggy code, insider attacks, misconfigured
services, and the creative construction of effective and sophisticated attacks not
envisioned by the implementers of security procedures. Building a secure and
trustworthy cloud computing environment is not enough, because attacks on data
continue to happen, and when they do, and information gets lost, there is no way to
get it back. There is a need to get solutions to such accidents.
The basic idea is that we can limit the damage of stolen data if we decrease the value
of that stolen data to the attacker. We can achieve this through a „preventive‟ decoy
(disinformation) attack. We can secure Cloud services by implementing given
additional security features.
5.1 Decoy System:
Decoy data, such as decoy documents, honey pots and other
bogus information can be generated on demand and used for detecting unauthorized
access to information and to poison the thief’s ex-filtrated information. Serving
decoys will confuse an attacker into believing they have ex-filtrated useful
information, when they have not. This technology may be integrated with user
behavior profiling technology to secure a user’s data in the Cloud. .
Whenever abnormal and unauthorized access to a cloud service
is noticed, decoy information may be returned by the Cloud and delivered in such a
way that it appear completely normal and legitimate. The legitimate user, who is the
owner of the information, would readily identify when decoy information is being
returned by the Cloud, and hence could alter the Cloud’s responses through a variety
of means, such as challenge questions, to inform the Cloud security system that it has
incorrectly detected an unauthorized access. In the case where the access is correctly
identified as an unauthorized access, the Cloud security system would deliver
unbounded amounts of bogus information to the attacker, thus securing the user’s true
data from can be implemented by given two additional security features:
1. Validating whether data access is authorized when abnormal information
access is detected
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2. Confusing the attacker with bogus information that is by providing decoy
documents.
We have applied above concepts to detect unauthorized data access to data
stored on a local file system by masqueraders, i.e. attackers who view of legitimate
users after stealing their credentials. Our experimental results in a local file system
setting show that combining both techniques can yield better detection results .This
results suggest that this approach may work in a Cloud environment, to make cloud
system more transparent to the user as a local file system.
5.2 Advantages of Fog computing
 Bringing data close to the user. Instead of housing information at data center
sites far from the end-point, the Fog aims to place the data close to the enduser.

Creating dense geographical distribution. First of all, big data and analytics
can be done faster with better results. Second, administrators are able to
support location-based mobility demands and not have to traverse the entire
network. Third, these edge (Fog) systems would be created in such a way that
real-time data analytics become a reality on a truly massive scale.

True support for mobility and the IoT. By controlling data at various edge
points, Fog computing integrates core cloud services with those of a truly
distributed data center platform. As more services are created to benefit the
end-user, edge and Fog networks will become more prevalent.

Numerous verticals are ready to adopt. Many organizations are already
adopting the concept of the Fog. Many different types of services aim to
deliver rich content to the end-user. This spans IT shops, vendors, and
entertainment companies as well.
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
Seamless integration with the cloud and other services. With Fog services,
we’re able to enhance the cloud experience by isolating user data that needs to
live on the edge. From there, administrators are able to tie-in analytics,
security, or other services directly into their cloud model.
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CONCLUSION
In Fog Computing we presenting a new approach for solving the problem of
insider data theft attacks in a cloud using dynamically generated decoy files and
also saving storage required for maintaining decoy files in the cloud. So by using
decoy technique in Fog can minimize insider attacks in cloud.
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Future of Fog Computing
With the increase in data and cloud services utilization, Fog Computing will play a
key role in helping reduce latency and improving the user experience. We are now
truly distributing the data plane and pushing advanced services to the edge. By doing
so, administrators are able to bring rich content to the user faster, more efficiently,
and – very importantly – more economically. This, ultimately, will mean better data
access, improved corporate analytics capabilities, and an overall improvement in the
end-user computing experience
Cisco’s Ginny Nichols coined the term fog computing. The
metaphor comes from the fact that fog is the cloud close to the ground, just as fog
computing concentrates processing at the edge of the network. According to Cisco,
fog computing extends from the edge to the cloud, in a geographically distributed and
hierarchical organization.
“Fog could take a burden off the network. As 50 billion objects
become connected worldwide by 2020, it will not make sense to handle everything in
the cloud. Distributed apps and edge-computing devices need distributed resources.
Fog brings computation to the data. Low-power devices, close to the edge of the
network, can deliver real-time response”says Technical Leader Rodolfo Milito, one of
Cisco’s thought leaders in fog computing.
“The Internet of Everything is changing how we interact with the
real world,” Milito added:“Things that were totally disconnected from the Internet
before, such as cars, are now merging onto it. But as we go from one billion endpoints
to one trillion endpoints worldwide, that creates not only a real scalability problem but
the challenge of dealing with complex clusters of endpoints – what we call ‘rich
systems’ – rather than dealing with individual endpoints. Fog’s hardware
infrastructure and software platform helps solve that.”
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REFERENCES
1.
http://www.cisco.com/web/about/ac50/ac207/crc_new/university/RFP/rfp1307
8.html
2. http://www.howtogeek.com/185876/what-is-fog-computing/
3. http://newsroom.cisco.com/featurecontent?type=webcontent&articleId=1365576
4. http://a4academics.com
5. https://en.wikipedia.org/wiki/Cloud_computing
6. https://en.wikipedia.org/wiki/Fog_computing
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