Fog Computing is the Future of the Industrial Internet of Things

In the last century, transportation, medical, power and industrial systems were built from individual devices, typically programmed one at a time. The Industrial Internet of Things (IIoT) is changing all of that, transforming isolated programmable devices into intelligent networks of connected machines, such as autonomous cars, intelligent drones, smart grid power systems, automated air traffic control, connected medical devices, robotic oil drilling and more. As a result, these systems have unique computing requirements including real-time processing, integrated security, high performance, reliability and scalability.

Although the Internet of Things (IoT) is driven by connecting field devices to the cloud, cloud computing models have limitations. Most IoT implementations are about connecting to, and doing all of the processing in, the cloud. Although this can work for the consumer IoT, in the Industrial IoT, not everything can take place in the cloud. It is imperative to move computing to the devices, to the operational edge. That's Fog.

Fog vs. Cloud for the IIoT

The cloud has traditionally been a major driver for the Industrial IoT because it offers a computing environment that can dynamically scale to meet the changing demands of robust industrial systems. Cloud offers key benefits: location transparency, ease of development, network connectivity and elasticity.

However, as the amount of IIoT data increases, transmitting it all to the cloud can lead to challenges such as high latency on the network, support of end-point mobility, loss of connectivity, unpredictable bandwidth bottlenecks and distributed coordination of systems and clients. Ideally, the intelligent software that drives these systems must also reside in the field, at the "operational edge," for when there is no time, bandwidth or reason to send data from these devices to the cloud. This is the challenge that Fog computing is solving by shifting computation closer to the device.

Fog computing is used to define the distributed computing, networking and storage that supports intelligence at the edge of the network. Fog computing moves computing closer to the applications, saving bandwidth on billions of devices and enabling the processing and analyzing of data closer to where the data is produced. Fog computing solves network challenges by supporting continual operations in remote locations and improves security by reducing the volume of raw data shared with the cloud over the internet.

Benefits of Fog Computing

Integrate intelligence Save development costs
Scale Enable system evolution
Improve reliability Connect IT to OT
Enforce security Improve safety
Enable new business models Optimize resource use
Respond to the real world Enable open architecture
Integrate many vendors Ease system integration
Prevent human error Reduce development risk

Autonomous Driving: An Example

An autonomous car system requires Fog computing because it involves high performance computing inside the car and outside of the cloud. The car's system takes in sensor data and processes it on-site rather than sending the information to the cloud to be processed. This way, the car's intelligent computing system can determine an action in real-time—for example, whether to hit the brakes or speed up—and doesn't rely on a connection to the cloud before making that decision. Fog computing is crucial in this environment because if the car were to lose connection to the cloud, the implications could be disastrous. These types of critical systems—that require response times of less than a millisecond—span top Industrial IoT industries including transportation, healthcare, robotics and energy.

Fog Computing and RTI Connext

These types of intelligent field systems will disrupt nearly every aspect of the industrial landscape. RTI's data-centric approach is the ideal technology for Fog computing, providing the scalability, speed, security and safety required by truly critical industrial systems. Connext DDS was built for this type of computing environment and RTI is committed to supporting industry software standards such as the OpenFog consortium.