A Horizontal Taxonomy for the Industrial IoT
In this framework, architectural approaches and the
technologies that implement them can be considered to
“occupy” some region in this N-dimensional space. For
instance, a data-centric technology like the Object
Management Group (OMG) Data Distribution Service
(DDS)2 provides peer-to-peer, fully-redundant connectivity
with content filtering. Thus, it would occupy a space that
satisfies many Reliable, Real-Time applications with
significant numbers of Data Items, the first three challenge
dimensions above. The Message Queuing Telemetry
Transport (MQTT) protocol, on the other hand, is more
suited to the data collection focus challenge. Thus, these
technologies occupy different regions of the solution space.
Figure 11 represents this concept in three dimensions.
Figure 11: N-Dimensional
Requirement Space
Architectural approaches and their
implementing technologies satisfy
some range of each of the dimensions
above, and thus occupy a region in an
N-dimensional “requirement space”.
The value of a taxonomy is to help
designers decompose their problem
into relevant dimensions so they can
then select an appropriate approach.
Thus, the application can be placed in the space and the
architectural approaches represented as regions. This
reduces the problem of selecting an architecture to one of
mapping the application point to appropriate architectural regions.
Of course, this may not be a unique map; the regions overlap. In this case, the process indicates
options. The tradeoff is then to find something that fits the key requirements while not imposing
too much cost in some other dimension. Thinking of the system as an N-dimensional mapping of
requirements to architecture offers important clarity and process. It greatly simplifies the search.
5.
TAXONOMY BENEFITS
Defining an IIoT taxonomy will not be trivial. The IIoT encompasses many industries and use
cases. It encompasses much more diversity than specialized industry, enterprise IT, or even
“consumer” IoT applications. Technologies also evolve quickly, so the scene is constantly shifting.
This work just scratches the surface.
However, the benefit of developing a taxonomical understanding of the IIoT is enormous.
Resolving these issues will help system architects choose protocols, network topologies, and
compute capabilities. Today, we see designers struggling with issues like server location or
configuration, when the right design may not even require servers. Overloaded terms like “real
time” and “thing” cause massive confusion between technologies despite the fact that they have
no practical use-case overlap. The industry needs a better framework to discuss architectural fit.
2
www.omg.org/dds
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