Enhancing intelligence with the Internet of Things
1. Enhancing Intelligence in the
‘Internet of Things’
The Business of Embedded Virtualization
Alexander Damisch, Director, Industrial Vertical, Wind River
INNOVATORS START HERE.
2. ENHANCING INTELLIGENCE IN THE ‘INTERNET OF THINGS’
EXECUTIVE SUMMARY
A key driver for embedded system designers is the cloud. With billions of devices becoming connected in the “Internet of things” and sharing data through the cloud, there is a
key challenge in managing this complexity. The amount of data that is moved around the
Internet is expected to double in just three years and there are different architectures for
addressing this challenge of sharing and managing data securely and reliably in the cloud.
This is a different situation from the existing migration of apps into the IT cloud. Systems
handling machine-to-machine (M2M) data have to be reliable, secure, and scalable with
real-time performance measured in microseconds. All this data has to be available anytime, anywhere, and this is opening up new ways for equipment to be designed and built.
This paper takes a look at the key industry trends driving consolidation of processing
workloads to make all the functionality on a device secure, manageable, and scalable.
TABLE OF CONTENTS
Executive Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
Industry Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
. .
Security . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
. .
Complexity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
. .
Virtualization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Smart Grid. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 ..
Manufacturing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Transportation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Consolidation and Separation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Scalability. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
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3. ENHANCING INTELLIGENCE IN THE ‘INTERNET OF THINGS’
INDUSTRY TRENDS
system grows in a haphazard, unmanaged way. Often the original
One architecture that is gaining ground is to provide more local-
elements of the system are so critical that there is no opportunity
ized, connected processing power close to where it is needed,
to pull everything out and start again from scratch, leading to a
often as a gateway to the wider Internet. In this way, local traffic
more evolutionary architecture.
can be processed quickly and acted on, while the data is still avail-
This often leads to a highly complex base of software that is con-
able to the wider systems across the Internet, whether it is a train,
stantly patched and not well documented, creating bugs, errors,
a manufacturing floor, or a power plant.
and glitches. The safety-critical elements of the design, from
At the heart of this approach is the ability to consolidate a num-
programmable logic controllers to sensors, tend to be relatively
ber of functions, from the communications to the data processing.
simple, well-tested devices that have well-defined code and states
This is costly and complex when implemented in separate boxes,
and are left alone. As a result, adding new functions and features
and the ability to consolidate a wide range of functions reliably
can often impact the overall performance of the system.
and securely into an intelligent single unit that is more cost effec-
All of this is reflected in higher costs for upgrading, managing, and
tive is increasingly popular.
protecting the system. With many industrial embedded systems
Security
not built with communications or security in mind, this is a signifi-
This trend has implications for security. Consolidating workloads in
a single device means communications are linked to real-time operations and the flow of data. This means there is a need to keep certain functions very separate. Safety-critical code has to be protected
and unchanged to retain its certification, and yet the security that
protects the system has to be updated regularly to defend against
ever changing attacks. At the same time, there are communications protocols and data capture in the system that need real-time
performance alongside human interfaces that can be run at slower
speeds.
All of this provides a potentially highly complex environment. The
traditional approach has been to have separate devices for each
of these functions, keeping communications and real- time elements separate. However, security needs to be deeply embedded
within the system to provide the maximum protection, and physical separation leads to a number of architectural challenges that
can be expensive to solve.
Complexity
cant part of the cost of doing business.
Virtualization
Virtualization has been solving a number of these challenges.
Using multiple cores and time and space separation it has been
possible to run the different elements—security, communications,
real-time, and user interface—on separate operating systems on
separate cores. Sometimes these separate cores are in separate
devices on a single board, replacing multiple boards in a system.
Increasingly, these elements have been coming together in a single
multi-core device, offering higher performance that can be used
for more features or lower power consumption, which is now a key
consideration. This trend is being supported with new approaches
such as virtualization extensions within processors capable of supporting time and space separation in hardware, increasing performance and reducing power consumption and system cost.
Now it is possible to run multiple operating systems and separate applications on a single core and still achieve the real-time
performance that many embedded industrial systems require. This
This separation tends to show up in system architectures in a
allows for significantly lower cost and complexity as well as lower
number of ways. Often it shows up with new devices being added
power consumption than with multi-core systems.
to the system to provide new features or new security, and the
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4. ENHANCING INTELLIGENCE IN THE ‘INTERNET OF THINGS’
Smart Grid
Manufacturing
The current industry focus on the smart grid is a classic example
Similarly, manufacturing plants can benefit from virtualization. A
of the challenges of adding intelligence and networking to exist-
single-core device can run several “soft” programmable logic
ing legacy systems. The concept of the smart grid is driven by the
controllers (PLC) and provide the security and communications
need to integrate variable power sources such as wind or wave
for sensors and networks around the shop floor through a real-
power into the existing power grid based around static sources
time operating system. Graphical interfaces can be added via the
such as traditional power stations. To do this requires “smart
non-real-time elements to make machines more user friendly and
meters” that measure consumption in the home, office, or factory
productive with an easy upgrade process that does not perturb
as well as a network to carry that data back and control the differ-
other parts of the systems.
ent parts of the grid based on the real-time data. This is a highly
complex task that requires large amounts of data handling and
processing power overlaid on a grid that was constructed in the
1950s or even earlier.
With the communications stacks implemented securely and reliably, all the data from around the floor can be available whenever
and wherever required. This can be used to make planning more
efficient and allow algorithms to spot potential problems within
While there are large scale data centre implementations for han-
the equipment, triggering preventative maintenance routines and
dling predictive algorithms, a vast amount of processing has to be
reducing costly downtime.
handled towards the edge of the grid. Potentially handling thousands of smart meters and sensors throughout the grid, this acts
as a gateway to the wider network and protects all those meters
and power systems from intrusion. Real-time performance is vital,
as is reliability and traceability of all the data when it is used for
billing purposes.
There is a very clear place for such gateways acting as servers for
the “client” meters, but the current multi-core devices can have
higher performance than necessary. The performance of single
core devices is now such that one device can run a secure realtime operating system such as Wind River’s VxWorks® that can
Transportation
Transport shows similar characteristics. Increasing amounts of electronics are making their way into transportation systems, especially
trains. New safety-critical braking control and signaling systems are
being implemented alongside data management and entertainment networks, all on a physical platform that is decades old. Costeffective commercial off-the-shelf (COTS) systems based around
single-core devices can now handle these key features such as train
information systems and other functions safely and securely.
Instead of having signals on the rail, trains now have their own
handle both data and communications stacks alongside a general
highly sophisticated signal and position management systems.
purpose operating system such as Microsoft Windows or embed-
Positive train control systems are adding highly connected intel-
ded Linux. This simplifies the system design and allows existing
ligence in trains, for example, making them position-aware as
code to be run safely and securely but also allows security to
well as providing a centralized advanced train control (ATC) man-
be updated regularly. New features and data handling routines
agement system. This ATC system is a key example of an M2M
can be added in the non-real-time portion of the design without
cloud architecture, taking data from trains around the network to
impacting on the real-time, security, or communications elements.
enhance the operation and safety of the system as a whole. Using
This dramatically reduces the complexity, risk, and costs of rolling
this connected distributed intelligence can improve safety and
out the infrastructure that is required for the smart grid.
performance but the challenge is to implement such a system cost
effectively.
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5. ENHANCING INTELLIGENCE IN THE ‘INTERNET OF THINGS’
Operational Control Center
High A
Authority
Management
Server
Remote
Users
Communications
Train Control
Training/Train
Controller/
Transit
Manager
Train
Control
Servers
*n
TCP/IP
Router
UPS
Authority
Server,
Trainborne,
Wayside
Trainborne
Diagnostic Support
GPS Location
Determination
Trackside
Crossing
Key
Local Communications
Wireless
Network
Defect
Detectors
Control
Point
Rail-Rail
Interfaces
Wayside Interface Units (WIUs)
Architecture of a positive train control system
Consolidation and Separation
Scalability
There are two areas where virtualization is particularly relevant:
A key element of virtualization is the scalability. Supporting mul-
providing consolidation of workloads and combining communica-
tiple operating systems on a single core means the system is eas-
tion stacks with other functions.
ily expandable to higher-performance multi-core devices with
Consolidation of workloads is at the heart of the move to having
all data accessible anywhere. Keeping real-time functions separate
from general data processing and handling is vital to maintaining systems’ responsiveness, but it all has to be kept secure. This
leads to new system architectures based around the dynamic flow
of data. Here, control, interface, security, and communications are
all kept separate as they all change at different rates and have
different requirements. Being able to combine these functions in
a single device and still keep them separate is a vital element in
providing design flexibility and agility.
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minimal risk. The multi-core device can handle the operating systems on separate cores, providing higher performance for more
advanced features without having to rewrite and retest the existing system implementation. This brings a dramatic savings in the
development time and costs of moving to a new generation of
equipment. This also allows vendors to provide scalable equipment platforms that are based around a common code base that
is tested and reliable.
