October 17
24
E
mbEddEd
C
omputing
Hardware for Industrial IoT fog
and mist computing
By JC Ramirez,
ADL Embedded Solutions
The latest industrial Intel Atom proces-
sors are empowering new, small form
factor systems for industrial appli-
cations. IIoT hardware optimization
using a bottom-up approach gathers
momentum and the ecosystem of
providers of fog and mist-computing
solutions gets new hardware.
Industrial IoT (IIoT) continues to expand
into the far reaches of the industrial and com-
mercial environment. In many of these envi-
ronments (think smart grid, wind farms, oil
and gas, autonomous vehicles, etc) reliable
connectivity to the cloud is plagued by inter-
mittent connectivity, latency and security
issues. Add to that the fragmented reality of
trying to build a cohesive IIoT cloud solu-
tion from the vast array of legacy and modern
equipment, machinery, control software, and
disparate databases, and the task begins to
take on monumental costs and time propor-
tions. To address some of these issues, recent
attention has turned to pushing IIoT hard-
ware, data storage, data analytics and commu-
nication resources nearer to the IIoT edge in
close proximity to the things being controlled.
First and foremost, this helps address inter-
mittent connectivity and latency issues result-
ing in better uptimes and overall efficiency,
but it also provides more optimal distribution
of resources and helps limit the scope of the
security task.
Social media conversation and many recent
articles have centered on these new IoT/IIoT
computing strategies. Extending the analogy
of the IoT/IIoT cloud in the meteorologi-
cal sense, this idea of moving IIoT resources
closer to the things being controlled is often
referred to as fog or mist computing. If fog
computing defines IIoT resources in close
proximity to things, mist computing defines
IIoT resources directly on or in things. Pro-
moted by the Open Fog Consortium with
founding members including Intel, ARM,
Cisco, and Dell, fog computing is defined as,
“...a system-level horizontal architecture that
distributes resources and services of com-
puting, storage, control and networking any-
where along the continuum from cloud to
things.” Fog computing addresses the needs of
IIoT at a local level providing distributed data
and control resources for increased efficiency
and reliability. Fog computing makes use of
new software-designed automation elements
like software-PLC controllers and digitization
of equipment and processes with sufficient
detail as to be termed, digital twins. These vir-
tual and digitization strategies are a key com-
ponent in addressing the fragmented state
of communication and control at the lowest
hardware levels.
Extending this analogy one step further, the
term mist computing is used to refer to those
compute, communication, and storage ele-
ments integrated directly into or onto machin-
ery and equipment thus extending IIoT
computing to the hardware level. According to
industry expert Angelo Corsaro, Ph.D. one of
the primary objectives for mist computing is
“...enabling resource harvesting by exploiting
the computation, storage, and communica-
tion capabilities available on the things.” Table
1 lists the typical hardware necessary at the
various IIoT computing layers. At the cloud
level, the hardware elements revolve around
server farms, immense in some cases, and
sophisticated enterprise-scale control centers
designed to store and analyze truly massive
amounts of data for management, control,
and monitoring of the enterprise down to the
factory floor. At the fog computing level, the
scale of the equipment takes on smaller pro-
portions via server rooms and local storage
supported by an array of smaller network-
ing elements including gateways, routers, and
industrial PCs with local databases enabling
local data analytics, monitoring and con-
trol of things. Mist computing completes the
resource migration picture by extending key
hardware elements of fog computing directly
onto or into things albeit in much smaller
embedded form factors. Beyond providing
the equipment control and monitoring func-
tion, this hardware must also support fog and
mist computing sharing of resources.
The reality of close proximity or direct phys-
ical integration onto/into things is no small
feat. From an environmental standpoint, the
hardware must be able to survive the same
environmental conditions (temperature,
humidity, mechanical stress, etc) as the things
Figure 1. With the ADLE-
3800SEC a Microsoft Azure
certified 75 mm x 75 mm Edge
Connect SBC with Intel E3800
ATOM processor is offered.
