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Use Cases Fog Computing

Fog Computing

Fog computing refers to a decentralized computing structure, where resources, including the data and applications, get placed in logical locations between the data source and the cloud; it also is known by the terms ‘fogging’ and ‘fog networking.’

The goal of this is to bring basic analytic services to the network edge, improving performance by positioning computing resources closer to where they are needed, thereby reducing the distance that data needs to be transported on the network, improving overall network efficiency and performance. Fog computing can also be deployed for security reasons, as it has the ability to segment bandwidth traffic and introduce additional firewalls to a network for higher security. 

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PubNub Aids in McDonald's Malaysian Campaign
PubNub Aids in McDonald's Malaysian Campaign
McDonald’s Save the Sundae Cone campaign had a McDonald’s Sundae Cone on the digital billboard, which was slowly melting in the heat of the city. To “save” the sundae cone, the audience needed to spin a giant fan that would ‘cool’ the sundae cone and ‘un-melt’ it. They did this by spinning a mini-fan, which was accessed through their mobile device’s web browser. At the end, participants were given a voucher on their smartphone to be redeemed at a McDonald’s across the street for a free sundae cone. The realtime network needed to be able to handle hundreds of users simultaneously, and with such a large audience, 100% uptime was vital for the campaign.
Koito - Reality AI: Next-generation Adaptive Driving Beam (ADB) smart headlight
Koito - Reality AI: Next-generation Adaptive Driving Beam (ADB) smart headlight
The current versions of Adaptive Driving Beams available in Japan and Europe are using traditional machine vision techniques like template matching. Those machine learning techniques perform very well in constrained environments but are prone to many false positive when used in the dynamic, real world, with a lot more variations in targets and backgrounds.
Powering Smart Home Automation solutions with IoT for Energy conservation
Many industry leaders that offer Smart Energy Management products & solutions face challenges including:How to build a scalable platform that can automatically scale-up to on-board ‘n’ number of Smart home devicesData security, solution availability, and reliability are the other critical factors to deal withHow to create a robust common IoT platform that handles any kind of smart devicesHow to enable data management capabilities that would help in intelligent decision-making

The edge analytics market is estimated to grow from USD 1.94 billion in 2016 to USD 7.96 billion by 2021, at a Compound Annual Growth Rate (CAGR) of 32.6%.

Source: Markets and Markets


What is the business value of this IoT use case and how is it measured?
Your Answer

What value do Fog Computing to companies?

By adding the capability to process data closer to where it is created, fog computing seeks to create a network with lower latency, and with fewer data to upload, it increases the efficiency at which it can be processed.

There is also the benefit that data can still be processed with fog computing in a situation of no bandwidth availability. It provides an intermediary between these IoT devices and the cloud computing infrastructure that they connect to, as it is able to analyze and process data closer to where it is coming from, filtering what gets uploaded up to the cloud.

What are the benefits of Fog Computing in real-time applications?

It is broadly used in IoT applications which involves real-time data. It acts as an extended version of cloud computing. It is an intermediate between the cloud and end users (closer to end users). It can be used in both the ways, that can be between machine and machine or between the human to machine.

- Mobile Big Data Analytics

- Water Pressure at Dams

- Smart Utility Service

- Health Data


What business, integration, or regulatory challenges could impact deployment?
Your Answer

What are the major challenges in Fog Computing?

Security challenges are predominant in fog computing. 

Fog computing considers the architecture of SOA. The network layer is established between the service layer and the application layer. Hence, Fog computing is designed ahead of traditional networking components, which are highly vulnerable security attacks.


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