Clearing the fog surrounding fog computing
Cloud Edge Computing or Fog Computing is a concept related to the IoT (Internet of Things) and the sending of data to the Cloud.
It’s best if we examine this concept alongside the other main cloud computing concept. For clarity we’ll name each after the 2 companies who are driving product development and innovation in each of the respective ways of thinking.
The Amazon IoT approach
Amazon advocate sending all data to the Cloud for processing. This approach is very much a “capture everything and deal with it later” way of thinking. Of course, Amazon have the infrastructure to deal with the massive amounts of data that will issue forth and many believe that collecting as much data as possible is the most robust method for future-proofing whether this data is useful now or not.
This “catch all” approach provides a safety net if in the future historical data is required. Nobody can predict the future but yesterday’s data may become a tool of competitive advantage in tomorrow’s world.
Advantages of Send-All-to-Cloud:
No data left behind (could be useful later)
Big Data tools for centralized analysis
The Dell IoT Cloud Edge Approach
Dell believes that the future of IoT lies at the Cloud Edge. Unlike Amazon’s “grab it all” approach to data, Dell take a more pragmatic “take only what is useful and meaningful, then send it to the Cloud” perspective. This is the essence of Edge Computing.
To conduct this cloud-edge processing of data, something has to be placed between The Cloud and the item collecting the data (placed at the Cloud’s edge as it were). This “in-between” item is known as an IoT Cloud Edge Processing device or a Cloud Edge Gateway. It can also be termed a Fog Computing Device (the fog at the edge of the Cloud)
Analyzing IoT data near to where it is collected cuts gigabytes from network traffic and keeps sensitive data inside the network.
Advantages of Cloud Edge computing:
Only the meaningful data is taken – lower data volume
Calculations can be performed on the data before it is sent
Lower bandwidth costs
Realtime processing
All this data, now what?
In both of these cases the overriding thing to keep in mind is that it is not the amount of data collected that is valuable. The value of data is in how it is interpreted and how it is used.
