cloud computing has achieved widespread adoption by companies across the board. It has been embraced by businesses that want to utilize the resources and capabilities of
large enterprises but, at the same time, reduce costs, decrease their IT infrastructure and work from remote locations on the Internet connected device of their choice.
The birth of cloud computing put the power of technology in the hands of non-technical men and women who can now store and analyze large quantities of data. They have the ability to scrutinize their most profitable customers and understand their buying habits, as well as implement new strategies like just-in-time inventory controls.
This new technology revolution has also spawned innovations like Big Data, BYOD (Bring Your Own Device), the Internet of Things and the consumerization of IT. These advancements, combined with the need to more accurately and quickly analyze vast quantities of information in real-time, have caused cloud computing to already become inadequate for certain applications.
So, if cloud computing, which has just recently achieved mainstream adoption, is already inadequate, what is the answer? What is the next technology innovation? It is fog computing.
Just like the real fog that you see in the sky which hovers between the ground and the clouds, fog computing takes place between end user devices which produce data
and the technology cloud located in a data center.
Rather than data traveling from a device like a car, an industrial robot or an exercise wristband all the way to a data center server for processing and analysis and then traveling back to the device for reporting, the processing and analysis is done on separate network devices which sit significantly closer to the source. Often called edge devices, they are located on the edge of the network in the fog rather than in the cloud. These edge devices can be placed anywhere with a network connection including a hospital’s emergency room or on an electrical pole on a street corner rather than needing to be housed in a corporation’s server room or data center.
Source: OpenFog Consortium
Although the cloud was designed to receive, process and store data, it is not equipped to handle the number of connected devices that are currently in use, the incredible volume and types of data they produce, and the rate at which we now generate that data.
The biggest challenges facing today’s modern cloud are latency and bandwidth issues. Because data must often travel long distances from the end user device to the data center for processing and storage, latency of even a few seconds can cause significant problems for applications requiring immediate feedback.
In addition, as the amount of data our devices generate continues to grow, the bandwidth needed to transmit and process that data will continue to grow while data transmission speeds and other network limitations remain the same.
Fog computing, on the other hand, takes the pressure off cloud computing by:
• Minimizing Latency: Milliseconds are critical when determining if a medical device needs to assist a patient with breathing or if a car should stop automatically when approaching a parked vehicle because the driver has not yet applied the brakes. The closer the analysis can happen to the device, the more quickly an informed response can be made.
• Preserving Bandwidth: It is unrealistic to think that current network infrastructures can successfully transport data from all of the devices which will require real-time data processing. Fog computing enables that processing and analysis to happen on edge devices much closer to where the data is created, and only transport select types and amounts of data to the cloud for long-term storage.
• Increasing Security: All data needs to be secured in transit to and from the cloud as well as in storage. The shorter the distance that the data needs to travel, the more secure it will be. In addition, a few industry regulations bar offsite storage of some data. Not only does fog computing significantly shorten the distance between the devices generating and processing the data, it also enables both devices to potentially be in the same building as in a manufacturing application where information from assembly line robots is generated and analyzed.
• Delivering real-time insights. Enabling the processing of data to take place closer to the source helps companies achieve actual, real-time data processing.
The Internet of Things (IoT) is defined as “the network of physical objects accessed through the Internet that contain embedded technology to sense or interact with their internal states or the external environment.”
Gartner predicts that 8.4 billion connected things will be in use worldwide by the end of this year and that the number will reach 20.4 billion things by 2020. Cisco goes even further with their forecast of 50 billion connected things by 2020, while still other firms predict a high of 250 billion. Whatever the actual number, the next 3-4 years will see explosive growth in the Internet of Things which will require fog computing to keep up the pace.
The extraordinary amount of IoT data that travel from the devices on which they are generated to the cloud for analysis, have two key requirements – immediate analysis and feedback, and continuous, long- term analytics. Fog computing is the answer to these needs for organizations including small businesses, healthcare providers, municipal ities, airlines, consumers, utilities, and more.
These are just a few examples that are becoming more commonplace every day. The possibilities and opportunities are endless.
The use of smart technology in our homes is understood by virtually everyone even if they are not specifically using the devices themselves. Ring’s video doorbell, the Amazon Echo, Rachio’s smart sprinkler, Phillips’ Hue home lighting, the August keyless door lock, and Keen’s Home Smart Vent are just a handful of the IoT driven products which have entered our homes. They each utilize fog computing to deliver faster response times, improved service, and enhanced safety.
Like the smart home, wearable technology has been enthusiastically embraced by consumers who wear Apple watches, Fitbit Charge HR health/fitness bands, and the Motorola Moto 360, among other devices.
Municipalities across the country are creating smart cities by applying IoT technology to environmental quality controls, traffic and parking enforcement, waste management, and water conservation and distribution. These IoT solutions increase efficiencies, eliminate traffic jams, decrease pollution, reduce expenses, increase parking availability and improve public transit operations.
From the monitoring of internal car systems to driving assistance, emergency management, driver safety, fleet management and predictive ma intenance, car manufacturers are continuously working to improve our safety, comfort, and overall driving experience.
Application opportunities for healthcare are vast as patients, physicians and healthcare facilities can all benefit. IoT devices connected to EHR systems help keep patients healthy and improve the level of care doctors provide while doctor’s offices, hospitals and other healthcare facilities are able to keep track of inventory.
The smart factory is moving beyond simple monitoring for impending equipment failure, to intelligent
product and supply chain management where systems coordinate the factory’s manufacturing and
distribution and update management on aftermarket services like product repairs.
From plane engines to wing flaps to landing gear, today’s planes are fully connected networks in themselves, delivering real-time information on performance and maintenance from takeoff to landing. Just one Boeing 787 jet can produce more than a third of a terabyte of data per flight.
Fog computing and the Internet of Things is the new technology frontier which is just now beginning to come into focus. Fog computing is not going to replace the cloud but act as a supplement to it, playing a critical role when needed but enabling the cloud to continue to play its role as well.
While fog computing and edge technologies meet the requirements for speed of analysis, deeper
insights and immediacy of response, cloud computing will continue to be used for analysis over time, big
data analytics and long-term storage. Both have their place in helping companies improve agility, lower costs and achieve their computing and business needs.