The Internet of Things (IoT) is revolutionizing the interconnection of devices, environments, and people, projected to create a $19 trillion market with 50 billion connected smart objects by 2020. Fog computing, or edge computing, processes data locally to reduce bandwidth usage, enhancing real-time responses and efficiency for applications like smart traffic systems and connected vehicles. This evolution addresses the shortcomings of traditional cloud computing by leveraging the resilience of smart edge gateways for better performance in an increasingly connected world.

1. IoT: A Fog-Cloud Computing Model
Internet of Things (IoT) represents a remarkable transformation of the way in which our world
will soon interact. Much like the World Wide Web connected computers to networks, and the
next evolution connected people to the Internet and other people, IoT looks poised to
interconnect devices, people, environments, virtual objects and machines in ways that only
science fiction writers could have imagined.

2. In a nutshell the Internet of Things (IoT) is the convergence of connecting people, things, data
and processes is transforming our life, business and everything in between.
There are some big numbers attached to this trend. Cisco optimistically predicted a $19 trillion
profit market for IoT, and projects there will be 50 billion smart objects connected to the Internet
by 2020. Clearly, those are motivating reasons for companies to put their label on this coming IT
tsunami.
The term fog computing is also referred to as “edge computing,” which essentially means that
rather than hosting and working from a centralized cloud, fog systems operate on network ends.
That concentration means that data can be processed locally in smart devices rather than being
sent to the cloud for processing. It’s one approach to dealing with the Internet of Things (IoT).
Fog computing, like many IT developments, grew out of the need to address a couple of growing
concerns: being able to act in real time to incoming data and working within the limits of
available bandwidth. Today’s sensors are generating 2 exabytes of data. It’s too much data to
send to the cloud. There’s not enough bandwidth, and it costs too much money. Fog computing
places some of transactions and resources at the edge of the cloud, rather than establishing
channels for cloud storage and utilization, it reduces the need for bandwidth by not sending every
bit of information over cloud channels, and instead aggregating it at certain access points. By
using this kind of distributed strategy, we can lower costs and improve efficiencies.

3. Fog Computing extends the cloud computing paradigm to the edge of the network to address
applications and services that do not fit the paradigm of the cloud including:
 Applications that require very low and predictable latency
 Geographically distributed applications
 Fast mobile applications
 Large-scale distributed control systems (smart grid, connected rail, smart traffic light
systems).
Defining characteristics of the Fog are: low latency and location awareness; wide-spread
geographical distribution; mobility; very large number of nodes, predominant role of wireless
access, strong presence of streaming and real time applications, heterogeneity.
The above characteristics make the Fog the appropriate platform for a number of critical Internet
of Things (IoT) services and applications, namely, Connected Vehicle, Smart Grid, Smart Cities,
and, in general, Wireless Sensors and Actuators Networks (WSANs).

4. Another way to look at Fog computing is to consider it a virtualized platform that is typically
located between end user devices and the cloud data centers hosted within the Internet. Thus fog
computing can provide better quality of service in terms of delay, power consumption, reduced
data traffic over the Internet etc. The main feature of fog computing is its ability to support
applications that require low latency, location awareness and mobility. This ability is made
possible by the fact that the fog computing systems are deployed very close to the end users in a
widely distributed manner. Fog computing nodes hosted must possess sufficient computing
power and storage capacity to handle the resource intensive user requests.
Fog computing in action
How does all of this work in the real world? Consider this example: A traffic light system in
Chicago is equipped with smart sensors. It is Tuesday morning, the day of the big parade after
the Chicago Cubs’ first World Series championship in more than 100 years. A surge of traffic
into the city is expected as revelers come to celebrate their team’s win. As the traffic builds, data
are collected from individual traffic lights.
The open-source application developed by the city to adjust light patterns and timing is running
on each edge device. The app automatically makes adjustments to light patterns in real time, at
the edge, working around traffic impediments as they arise and diminish. Traffic delays are kept
to a minimum, and fans spend less time in their cars and have more time to enjoy their big day.
In the traffic light example, there is little value in sending a steady stream of everyday traffic
sensor data to the cloud for storage and analysis. The civic engineers have a good handle on
normal traffic patterns. The relevant data is sensor information that diverges from the norm, such

5. as the data from parade day. That data would be sent up to the cloud and analyzed, supporting
predictive analysis and allowing the city to adjust and improve its traffic application’s response
to future traffic anomalies.
Fog, Cloud and IoT together
The IoT promises to bring the advantages of cloud computing to an earthly level, permeating
every home, vehicle, and workplace with smart, Internet-connected devices. But as dependence
on our newly connected devices increases along with the benefits and uses of a maturing
technology, the reliability of the gateways that make the IoT a functional reality must increase
and make uptime a near guarantee.
Using robust edge gateways would strengthen the entire IoT infrastructure by absorbing the
brunt of processing work before passing it to the cloud. Fog computing can meet requirements
for reliable low latency responses by processing at the edge and can deal with high traffic
volume by using smart filtering and selective transmission. In this way, smart edge gateways can
either handle or intelligently redirect the millions of tasks coming from the myriad sensors and
monitors of the IoT, transmitting only summary and exception data to the cloud proper.
The success of fog computing hinges directly on: the resilience of those smart gateways directing
countless tasks on an internet teeming with IoT devices. IT resilience will be a necessity for the
business continuity of IoT operations, with redundancy, security, monitoring of power and
cooling and failover solutions in place to ensure maximum uptime. According to Gartner, every
hour of downtime can cost an organization up to $300,000. Speed of deployment, cost-effective
scalability, and ease of management with limited resources are also chief concerns.
This evolutionary shift from the cloud to the fog makes complete sense. The original cloud boom
began when mobile devices like smartphones and tablets were becoming all the rage. Back then,
these devices were weak on computing power, and mobile networks were both slow and
unreliable. Therefore, it made complete sense to use a hub-and-spoke cloud architecture for all
communications.
But now that most of us are blanketed in reliable 4G technologies, and mobile devices now rival
many PCs in terms of computational power, it makes sense to move from a hub-and-spoke model
to one that resembles a mesh or edge computing data architecture. Doing so eliminates
bandwidth bottlenecks and latency issues that will undoubtedly cripple the IoT movement in the
long run.
So if you thought that cloud computing was the pinnacle of infrastructure designs for the
foreseeable future, think again. If we're talking billions of devices and instant communication,
current cloud models won't be able to handle the load. Fortunately, advances in mobile
processing power and wireless bandwidth have allowed many to design a far more capable
architecture that brings us out of the clouds and into the fog.