This presentation explains Fog Computing, which extends the cloud to where the "things" are. CONTENTS Simple Introduction Intro in Technical Language Fog Computing vs Cloud Computing Benefits Need Working Role of Cloud in Fog Computing Edge vs Fog Computing Use Limitations Conclusion

1. Fog Computing
What, How and Why
by
SHAKEEB AHMAD
SHAIKH ABUZAR

2. What is it?
• It defines a mix of a traditional centralized data storage system and
Cloud.
• Computing is performed at local networks, although servers
themselves are decentralized.
• The term fog computing was coined by Cisco
• The fog extends the cloud to be closer to the things that produce and
act on IoT data.

3. Extend the Cloud to Where the Things Are

4. In technical language
• These devices, called fog nodes, can be deployed anywhere with a
network connection: on a factory floor, on top of a power pole,
alongside a railway track, in a vehicle, or on an oil rig.
• Any device with computing, storage, and network connectivity can be
a fog node.
• Analyzing IoT data close to where it is collected minimizes latency.
• It offloads gigabytes of network traffic from the core network.
• It keeps sensitive data inside the network.

5. Fog computing vs cloud computing
• The data, therefore, can be accessed offline because some portions of
it are stored locally as well.
• This is the key distinction between fog computing vs cloud computing,
where all the intelligence and computing are performed on remote
servers.
• Rephrased: The main difference between cloud computing and fog
computing is that the former provides centralized access to resources
whereas the latter provides a decentralized local access.

6. Benefits?
• Low latency
• The fog network can process large volumes of data with little-to-no delay.
• Because a lot of data is stored locally, the computing is performed faster.
• Better data control
• In cloud computing, third-party servers are fully disconnected from local networks, leaving
little to no control over data.
• In fog computing, users can manage a lot of information locally and rely on their security
measures.
• A flexible storage system
• Fog computing doesn’t require constant online access
• The data can be stored locally or pulled up from local drives — such storage combines online
and offline access.
• Connecting centralized and decentralized storage
• Fog computing builds a bridge between local drives and third-party cloud services, allowing a
smooth transition to fully decentralized data storage.

7. Why do we need it?
• Smart sensors and IoT devices generate immense amount of data, which
would be costly and time-consuming to send to the cloud for processing
and analysis.
• Fog computing reduces
• bandwidth needed
• back-and-forth communication between sensors and the cloud
• which can negatively affect IoT performance
• Although latency may be annoying when sensors are part of a gaming
application, delays in data transmission in many real-world IoT scenarios
can be life-threatening
• Security shortcomings: Existing data protection mechanism in cloud
computing such as encryption failed in securing the data from the attackers

8. How it works
• Fog computing works by deploying fog nodes throughout your
network.
• Devices from controllers, switches, routers, and video cameras can
act as fog nodes.
• These fog nodes can then be deployed in target areas such as your
office floor or within a vehicle.
• When an IoT device generates data this can then be analyzed via one
of these nodes without having to be sent all the way back to the
cloud.

9. Working (…continued)
• Transporting data through fog computing has the following steps:
• Signals from IoT devices are wired to an automation controller which then
executes a control system program to automate the devices.
• The control system program sends data through to an OPC server or protocol
gateway.
• The data is then converted into a protocol that can be more easily understood
by internet-based services (Typically this is a protocol like HTTP or MQTT).
• Finally, the data is sent to a fog node or IoT gateway which collects the data
for further analysis. This will filter the data and in some cases save it to hand
over to the cloud later.

11. Role of cloud in fog computing
• The primary advantage of cloud-based systems is they allow data to be
collected from multiple sites and devices, which is accessible anywhere in
the world.
• Cloud computing is the standard of IoT data storage right now. It’s the form
of computing where data is stored on multiple servers and can be accessed
online from any device. Instead of saving information to the local hard
drive on a single computer, users store it on third-party online servers.
• To access data, a user needs to enter an account associated with the cloud
service. The data undergoes end-to-end encryption, so even service
providers have no access to the user’s contents. For the Internet of Things,
this means securely storing and managing a lot of data and having
immediate access to it from multiple devices, anytime, anywhere.

13. Edge vs Fog computing
• The key difference between the two lies in where the location of
intelligence and compute power is placed.
• A fog environment places intelligence at the local area network (LAN).
• Edge computing places intelligence and processing power in devices such as
embedded automation controllers.
• Edge computing processes data away from centralized storage,
keeping information on the local parts of the network — edge
devices. When the data is sent to the edge device, it can be processed
directly on it, without being sent to the centralized cloud.

14. Few insights
• How do fog and edge computing work?
• Fog computing is useful when the Internet connection isn’t always stable. For instance, on
connected trains the fog system can pull up locally stored data on areas where the Internet
connection can’t be maintained.
• How is data processed by fog computing?
• Urgent requests are sent directly to the fog and processed locally in the network;
• Less sensitive data is transferred to the cloud’s main data centers where it’s stored and analyzed;
• Under normal conditions, the majority of data goes to the cloud, local storages are used in
scenarios where saving bandwidth is a priority.
• Fog computing allows to implement data processing at the local networks, especially if it has to
be processed in real time. This is what makes this storage form incredibly stable under stressful
conditions, especially when comparing cloud vs fog computing.
• Edge computing is the least vulnerable form of decentralized storage. On the cloud, data is
distributed to dozens of servers, whereas edge computing uses hundreds, possibly thousands of
local nodes. Each device can act as a server in the edge network. To break into, hackers would
need access to thousands of destributed devices, which is practically impossible.

15. Use Cases
• Oil and Gas
• Energy and Utilities
• Hospitality
• Retail
• Wearables
• Smart buildings
• Agriculture
• Government
• Military

16. Limitations
• Physical location – Perhaps the most significant limitation of fog computing is
that it is much more geographically restrictive than a cloud service. A cloud
service can be accessed from anywhere whereas fog computing is used to
interact with devices on a local level. It doesn’t have any centralized access.
• Security – Another key concern is that of security. Fog computing relies on
trusting those close to the edge of the network and the fog nodes to maintain
them and protect them against malicious entities. The lack of visibility of these
systems due to their physical location can leave enterprises open to external
threats.
• Complexity – If you’re using a network with traditional infrastructure, cloud
services, and fog computing, things can get very complex very quickly. All of this
architecture needs to be maintained, and adding a patchwork of these complex
technologies together makes this a very difficult task

17. Conclusion
• Fog computing makes it easier for the engineers to focus on data and
handling the data instead of designing and maintaining the
architecture.