The Doppler Quarterly Special Edition 2019 | Page 56

WHY CLOUD
IS MAKING
COMPUTING
AT THE EDGE
RELEVANT AGAIN
It’s been a common problem for years. If you gather large
amounts of data from a device or other source, and you
need to process that data instantly, then moving it to a cen-
tralized database each and every time introduces latency. remote server that can be thousands of miles away. To
make matters worse, we send it over the open Internet.
However, considering the amount of processing that needs
to occur, the cloud may offer the best bang for the buck.
IoT must deal with this issue time and again. For example,
say there is a machine on a factory floor that analyzes the
quality of an auto part that it makes. If the part is not up to
specification, as determined by an optical scanner, then it’s
automatically rejected. While this keeps a human from look-
ing at the part, and thus slowing down the process, it also
takes a great deal of time. The system must transmit the
data and image back to the centralized database and com-
pute engine where a determination is made as to the suc-
cess of the manufacturing process. Then the results are
communicated back to the machine. Overcoming the Latency Challenge
The cloud complicates this process even more. Instead of
sending the data back to the data center, it is sent to a
54 | THE DOPPLER | SPECIAL EDITION 2019
To address the latency problem, many suggest “computing
at the edge.” It’s not a new concept, but it’s something that
was recently modernized. Computing at the edge pushes
most of the data processes out to the edge of the network,
close to the source. Then it’s a matter of dividing the work
between data and processing at the edge, versus data and
processing in the centralized system.
The concept is to process the data that needs to quickly
return to the device. In this case, it’s the pass/fail data that
indicates the success or failure of the physical manufactur-
ing of the auto part. However, the data should also be cen-