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Fog Computing: Answering the IoT Challenge

Fog Computing is being touted as the data communication solution our Internet of Things (IoT) devices are asking for by bringing the power of cloud computing closer to the end user. The fact is, the number of connected devices is going to continue to grow exponentionally. In fact, Gartner predicts that by 2020 IoT will include 26 billion connected things. Consider the impact that amount of data collected and processed will have.

Fog Computing: IoT by 2020http://wavelengths.freewave.com/wp-content/uploads/2016/06/17131d1461510... 300w" sizes="(max-width: 550px) 100vw, 550px" />

The Challenge

Naturally, with billions of devices all connected to the cloud for manufacturing, oil and gas, utilities, municipalities and enterprise, to name a few, the data transmission and processing rate is bound to slow down – especially if the current cloud architecture is upheld. Some IoT devices use the cloud to store data long term, where other connected things send data to the cloud to be analyzed and sent back to the device with operational instructions. Ahmed Banafa with SemiWiki explains, “As dependence on our newly connected devices increases along with the benefits and uses of a maturing technology, the reliability of the gateways that make the IoT a functional reality must increase and make up-time a near guarantee.”

Fog Computing Explainedhttp://wavelengths.freewave.com/wp-content/uploads/2016/06/17128d1461509... 300w" sizes="(max-width: 620px) 100vw, 620px" />

What is Fog Computing?

Fog Computing is a term coined by Cisco, that offers a way to analyze the data closer to the IoT device, thus saving valuable milliseconds. It may be hard to believe, but a millisecond has the power to prevent a M2M line shut-down, increase the speed at which power is restored to utilities and prevent an oil rig from leaking, just to name a few.

An easy way to visually understand where Fog Computing fits in our IoT M2M world, is by looking at the diagram above. It clearly shows that Fog Computing hangs between the cloud and the device, much like the fog on an early San Francisco morning.

Fog Computing operates at the network edge, extending the cloud capabilities closer to the source (IoT device). Each IoT connection works with what’s called Fog Nodes to digest the intelligent data and then coordinate operational next steps, whether that be acting directly and or transmitting results to the cloud. The diagram below covers the types of response times IoT devices face from both Fog Nodes and main cloud locations.

Fog Computing Nodeshttp://wavelengths.freewave.com/wp-content/uploads/2016/06/17129d1461509... 300w" sizes="(max-width: 620px) 100vw, 620px" />

Fog Computing Brings Efficiency to Enterprise

A recent report by Machina Research highlights the companies that pioneered Fog Computing and those poised to capitalize on the benefits in their near future. These companies are able to control the intelligent data at the edge of the network, saving time and creating a more stream-line approach to sending and receiving data efficiently and more securely.

Overall, as our need to connect explodes, we will not only need to think about IoT, but also the way in which intelligent data is processed from the critical infrastructure and back to the cloud. Fog Computing will continue to open more efficient channels across our IoT, as long as we allow it.

 

The post Fog Computing: Answering the IoT Challenge appeared first on FreeWave WaveLengths.

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More Stories By Scott Allen

Scott is an executive leader with more than 25 years of experience in product lifecycle management, product marketing, business development, and technology deployment. He offers a unique blend of start-up aggressiveness and established company executive leadership, with expertise in product delivery, demand generation, and global market expansion. As CMO of FreeWave, Scott is responsible for product life cycle/management, GTM execution, demand generation, and brand creation/expansion strategies.

Prior to joining FreeWave, Scott held executive management positions at Fluke Networks (a Danaher Company), Network Associates (McAfee), and several start-ups including Mazu Networks and NEXVU Business Solutions. Scott earned his BA in Computer Information Systems from Weber University.

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