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The Internet of Things and the Importance of Modeling
and Simulation
A look at why modeling and
simulation capabilities are becoming an indispensable element of the Internet
of Things toolbox. From http://www.cdait.gatech.edu/
By Dr. Margaret L. Loper and
Alain Louchez , Georgia Institute of Technology, on August 3, 2015
Among the plethora of projections
concerning the Internet of Things (IoT), the pervasive thread in all of them is
the sheer size of the expected associated market a few years hence. While the
path to get there is still marred with uncertainty and uneasiness on how the
whole process is going to unfold, there is common agreement that in a world
where almost anything and everything is becoming potentially connectable the
number of communications links and smart endpoints (sensors, actuators, etc.)
as well as the induced complexity will be of a significantly different order of
magnitude from those currently experienced.
But there are other considerations.
Multifaceted Complexity
By its very nature, IoT is entering a completely new territory (especially in consumer IoT) that is not fully mastered. At the same time IoT technologies aim at integrating (everyday) objects into the communications space, they also bring about a new set of challenges. For example, when it comes to wearables, new antennas and connectors in all kinds of form factor must be designed, with possible non-trivial ergonomic and health implications.
In addition, as it has been widely reported, IoT devices
are also vulnerable to cyberattacks, sometimes with devastating consequences
including but not limited to privacy breach. This risk needs to be rigorously
researched and minimized.
As a result, the way IoT solutions
are going to be designed, developed and deployed is bound to go through a
radical transformation. Related methods and procedures will have to incorporate
sound and thorough analysis, and technological and financial considerations
will dictate that IoT innovations be modeled and simulated before going live.
As far as IBM is concerned, modeling
and simulation (M&S) is already core to IoT’s “here and now”: “Modeling and
simulation is a vital ingredient in creating the connected products at the
heart of the Internet of Things. It can support early evaluation and
optimization of designs and ongoing verification as changes occur—to make sure
the right product is developed and delivered with the required speed and
quality” (IBM website).
The human mind is lazily comfortable
with linearity, for instance when “things will change the same way they did in
the past”. In this type of environment, forecasting is straightforward;
modeling is simple and simulation does not provide useful insight.
However, in a universe fraught with
“nonlinearities” of the kind shaped by a fast-growing pool of intelligent
objects interacting with each other and submitted to a variety of contingent
disturbances, extrapolations are no longer clear-cut. We are all experiencing
this type of random output in traffic-related situations: how many times have
we done things early “to beat the traffic”, well aware that during peak-hours
leaving ten minutes later does not necessarily mean arriving at destination ten
minutes later? Given the IoT complexity and scale, M&S is no longer a
luxury, it is a necessity.
IoT System Engineering Essential
Requirement
By many accounts, the Internet of Things is viewed as a “system of systems” or even “systems of systems”. Like in any other system engineering endeavor, M&S is a critical foundational building block; it is used early in the lifecycle to determine the efficacy of a proposed product. It is an effective means of defining product requirements, and can be used to test and confirm the viability of meeting requirements, as well as to verify the performance of a product.
M&S is all the more needed since
it takes place among the continuous and unstable interaction between
enterprises and their environment. Enterprises are complex adaptive
socio-technical systems. They consist of many independent agents, whose
behavior can be described by social, psychological, and physical rules, rather
than dictated by the dynamics of the entire system. The overall enterprise
system adapts and learns often resulting in emergent patterns and behaviors.
Given that no single agent is in control, complex enterprise system behaviors
are often unpredictable and un-controllable.
It follows that creating a model,
executing a simulation and performing experimental runs should become
prerequisite steps in any IoT-related project or undertaking.
Use cases abound in the IoT
ecosystem where M&S sheds useful light on the contemplated project.
Healthcare, manufacturing and traffic management are a few examples among many
where M&S is growingly playing a key role. M&S is critical to
understand their complex issues, and support exploration of a wide range of
decision possibilities in these systems.
Healthcare providers are faced with
a fundamental transformation of the way they get paid for their services – pay
for outcome is replacing fee for service. As financial incentives evolve,
providers must concentrate on prevention and wellness to diminish risks of
chronic diseases. M&S enables quick and cost-effective exploration of
alternative healthcare delivery mechanisms (including use of IoT technologies)
and their impact on key economic and health outcomes.
Researchers at
the 8th International Conference on Digital Enterprise Technology in Stuttgart,
Germany in March 2014, that was focused on disruptive innovation in
manufacturing engineering towards the 4th industrial revolution (embodied in
the arrival of the Internet of Things) outlined that “the simulation-based
technologies constitute a focal point of digital manufacturing solutions, since
they allow for the experimentation and validation of different product, process
and manufacturing system configurations.” M&S is also helpful for global
manufacturing, which is increasingly characterized by complex supply chains
providing components and subsystems that are eventually combined to form final
systems products for customers. One type of related risk is the possibility of
counterfeit parts, designed either with malicious intent or intent to defraud,
which can seriously impact product reliability, safety and lifecycle cost.
Comprehensive upfront M&S provides a referential non-defect baseline.
Traffic congestion is a primary
issue facing many of today’s urban and suburban areas. M&S can provide
transportation facility managers with real-time and near-future arterial performance
measures. For example, an approach using online data driven, microscopic
traffic simulation utilizing point sensor data can provide real-time
performance measures. Combining current and forecasted performance information
will enable greater efficiency in the use and operation of existing
transportation facility capacity.
Modeling and Simulation Are Central
to the Return on Investment
While it makes technological sense to walk before running, i.e., to model and simulate before deploying, it must also make financial sense. Akin to insurance, M&S looks expensive before adversity strikes. IoT-focused businesses must understand that embracing M&S in project development and management is good business practice. A systematic process must be established.
It is noteworthy, perhaps as a
guiding path for the private sector, that even at the Department of Defense,
where M&S is a vital enabler of successful military operations, the need
for well-structured, ROI-like metrics is paramount: “successful Department of
Defense (DoD) Enterprise modeling and simulation (M&S) investment requires
structure, persistence, and common valuation for effective execution.” (See:Calculating Return on Investment
for U.S. Department of Defense Modeling and Simulation, I. Oswalt et al., April
2011).
Next steps
M&S is a broad discipline with a wide range of technologies and methodologies. Academic and business resources in the field typically focus on a specific aspect with a different purpose (e.g., discrete event simulation in industrial systems vs. continuous simulation in electrical and computer engineering). There is a need for an all-encompassing approach, especially in the IoT arena.
M&S education and training might
become even more critical as the effects of the IoT revolution, as recently
underlined by Henry Kissinger in his latest book (“World Order”, Penguin Press,
New York, 2014, p.343) “extend to every level of organization /../ and
governments, wary of ceding the new field to rivals, are propelled outward into
a cyber realm with as yet few guidelines or restraints.”
We could very well imagine that a
battery of additional M&S-based tests might be required to verify that the
injection of IoT devices in cyberspace does not increase the national cyber
vulnerability. Currently, Machine-to-Machine (M2M)/IoT devices already need to
comply with a broad array of certification requirements coming from government
agencies (e.g., in the US, FCC, to make sure that the device does not emit
interfering signals), associations (e.g., PTCRB (PCS Type Certification Review
Board) to ensure that the device does not harm the cellular network), carriers
(e.g., radiation tests specific to each operator) and possibly other entities.
“Cyberspace has become strategically
indispensable. At this writing, users, whether individuals, corporations or
states, rely on their own judgment in conducting their activities,” Kissinger
observes. “The Commander of U.S. Cyber Command has predicted that ‘the next war
will be in cyberspace.’ It will not be possible to conceive of international
order when the region through which states’ survival and progress are taking
place remains without any international standards of conduct and is left to
unilateral decision” (“World Order”, p. 346).
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