IoT, for all its momentum, is still quite nascent. It holds vast promise for businesses (particularly in the manufacturing, energy, healthcare, logistics, and utilities industries) in that it can provide visibility into assets and help react to events faster. But the overwhelming volume, variety, and velocity of data it produces often outstrips bandwidth and exceeds the storage, computing, and sophisticated analytical capabilities of even the most advanced enterprises. Also, the fact that it takes so long for sensor data to travel through a gateway into the cloud, where businesses usually store and analyze it, limits the utility of connected solutions to a large extent.
If an IoT device slapped onto an industrial piece of equipment sends out alerts indicating the possibility of a machine failure, the info is only of value if the firm is able to act on it immediately; if technicians are dispatched too late and fail to take corrective actions in time this might lead to an operational disruption and even a production line shutoff.
In this post, we’ll discuss how low latency, excessive bandwidth consumption, and other IoT business issues can be addressed efficiently through a computing paradigm known as Fog; we’ll explain how data processing can be brought closer to the network’s edge and the immense benefits this brings in terms of core network traffic offloading.
Let’s get to it!
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