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An Optimal Path for the Internet of Things By @DaveGinsburg | @ThingsExpo #IoT

Is IoT only dribs and drabs of data across a cellular network, or is it more?

An Optimal Path for the Internet of Things
By Dave Ginsburg

To-date, we’ve deployed our technology for enterprise file sharing, backup and recovery, voice, ad serving, and financial services.  But what’s next?  If we look out a year or two, how does our solution intersect the Internet of Things?  Is IoT only dribs and drabs of data across a cellular network, or is it more?   The figure below from the GSMA segments IoT into three buckets, and provides some insight.

Fixed applications requiring low latency include both high bandwidth services such as surveillance, as well as lower bandwidth services such as the smart grid.  But it isn't just getting the data to-and-fro.  A central premise of IoT is being able to action the data in real-time, possibly through some evolution of IBM's Watson.   Within IoT, in most cases the remote device is not truly intelligent due to cost, power, or size.  The intelligence lies in the cloud, and the quicker the data from one or even a million devices can be ingested and analyzed, the quicker action may be taken.

An Optimal Path for the Internet of Things

In an electricity, natural gas, or water distribution network, a single sensor noticing an anomaly may not be enough, it may not have the context that something larger is at play. Distributed sensors in combination with cloud intelligence are quicker to react to any system-wide instability or may identify the source of a contaminant.   For the first time, closed-loop control that has existed in factories and power plants may now extend into the wide-area.  Alternatively, surveillance may transition from after-the-fact to actionable in real-time.  Local law-enforcement will have access to a live feed of a person or object identified as suspect.

Moving from the machine to the man, one could imagine a wristband monitoring a myriad of vital signs and chemistry.  These are all transmitted to the cloud, analyzed, and if out of equilibrium, help may be summoned or even action taken quicker than the individual could react on his or her own.

The use cases above all imply reach, unpredictability, access to resources most likely held within multiple cloud operators and data centers in real-time, and where necessary, interfaces to even more centralized expert systems.  It would be too costly and complex to attempt to provision a network for guaranteed performance, but what is possible is to leverage the cloud to offer optimal performacne at any point in time.  Throughput, latency, and loss may then be held within certain tolerances, permitting proper application behavior.   This is the goal of the Teridion Cloud Network.

Extending out from core IoT use cases, a second document from the GSMA does a great job of outlining 5G services, some of which may of course be handled by fixed networks as well.  Gaming, video, and virtual reality may all benefit from more assured delivery but due to reach don't lend themselves to pre-provisioned networks or content delivery networks.

Ultimately, any application can benefit from a network architecture that directs traffic onto the optimal path.


Read the original blog entry...

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