These are complex societies, complete with clear divisions
of labor, the ability to exploit new food sources and defend the nest from
enemies, and the capacity to move the entire community to a new nest location
if necessary. But there is no centralized "command and control" by
the queen or any other individual.
In place of any centralized control are a set of
highly-evolved behaviors that each individual is essentially born with. Ant
workers begin these tasks from the moment they emerge as recognizable adults,
often immediately beginning to care for nearby young in the brood chamber. No
on-the-job training, no instruction from mission control, no learning. They
simply operate.
Often worker activities are guided by a simple algorithm
selecting from a small set of choices based on situation. For example, an ant
worker encountering a hungry larva in the brood chamber feeds it. If the same
ant encounters the same larva outside the brood chamber, she carries it back to
the brood chamber, hungry or not. A relatively small set of these
highly-evolved simple decision trees is multiplied by thousands (or even
millions) of workers and then integrated in the form of the colony to result in
a highly adaptive, seemingly very intelligent SuperOrganism. But the actual
decision-making process of any individual
worker is very simple.
These basic principles of individual simplicity and
collective sophistication could be mirrored in the structure of the Internet of
Things. End devices may be outfitted with only the barest of intelligence,
simply broadcasting their state or responding to simple direction from other
functions. Meanwhile, intermediate devices in the Internet of Things may be
forwarding messages as necessary to effect communications throughout the
system.
A key to keeping the overall architecture simple may be
gleaned from the uncomplicated social insect decision process outlined above. A
basic set of communication and networking rules, multiplied billions of times
over in devices throughout the Internet of Things, may yield great
sophistication in overall function. Each individual ant does very little
"computing" – the same may be true for many members of the Internet
of Things.
One other factor has led to the incredible success of many
social insect colonies: the relatedness of the workers in the colony. In many
cases, the workers are all sisters of the same parents. This makes them very
closely related to one another. Because of this (and because workers typically
don't reproduce), there is no incentive for competition with nest mates. Thus,
the various classes of workers (or castes) perform a variety of duties on one
another's behalf selflessly. No external control is needed to guide the colony
to maximize its environmental fitness.
In contrast, the Internet of Things is being architected by Homo sapiens, whose innate drive for
competition with one another is adaptive and tragically well-documented. If
this competition (one might label it "greed" if uncharitable) is
reflected in the architecture of the Internet of Things, a great opportunity
will be lost.
If instead devices in the Internet of Things can be designed
to "help out" other devices (when the costs to do so are low); there
will a tremendous benefit to the network as a whole. This might take the form
of forwarding messages for unrelated devices or other means of insuring better
overall function at a minor cost of delay or compute power. Thinking like the
humble ant might prove to have great power in the Internet of Things.
Some writers have used ideas
from nature simply as metaphors for the IoT, while still others make a more
meaningful link to network engineering. I believe that the latter are on
the right track: architecting the Internet of Things based on successful
natural models of massive systems offers many possibilities.
In the next posts, I may move off communications for a while and explore other areas of the IoT.
