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Fog Computing: Distributing Intelligence and Data Collection to Edge Computing Elements
Fog computing is the distribution of computing tasks and ability to take actions to the computers that are closer to where data is being captured. It means that less data gets sent back to central cloud computers and the processing load at central computers is reduced. Because there are many more points of processing and less data is transferred, analysts believe the architecture will improve overall security and enable better scalability for Internet of Things (IoT). The term Fog Computing was originally coined by Cisco.
Cisco said that “the fog extends the cloud to be closer to the things that produce and act on IoT data. Fog applications are as diverse as the Internet of Things itself. What they have in common is monitoring or analyzing real-time data from network-connected things and then initiating an action.”
The so-called distributed edge computers are expected to become increasingly more common. IDC predicts that by 2020 about 10 percent of data and computing power will be located at the edge. A group called the Open Fog Consortium has started and is attempting to bring standardization around the ideas of fog and edge computing.
A recent article by Nanalyze describes five example use cases where the use of edge/fog computing would be beneficial: mining, wind farms, trains, pipelines, and oil wells. Other examples include Smart cities, lighting and parking, and port management.
David King, CEO of FogHorn Systems, describes how their business focuses on enabling “high-performance edge processing, optimized analytics and heterogeneous applications to be hosted as close as possible to the control systems and physical sensor infrastructure that already pervade the industrial world. By providing a software platform to process data directly on distributed, small-footprint edge devices (or sensors) rather than sending all data to a remote data center or distant cloud storage repository for processing, our technology minimizes latency and empowers IoT developers to create breakthrough real-time remote monitoring, asset optimization, proactive maintenance and operational intelligence applications.”
