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IoT security, connected cars, cloud tools, MEMS, wearables, and more in Embedded Computing Design February
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FeBRUARY 2015VOLUME 13
embedded-computing.com
#1
PLUS
SiliconBalancing power and performance in wearables pg. 12
StrategiesCan connected cars be secure cars?pg. 21
Sensor-enabled nodes support
the IoT for smart buildings and
smart transportpg. 26
IoT IssuePG. 31
The Internet of Things: It's a connected world
Network Security Appliance
PICMG SBC
1-877-278-8899
Mini-ITX Small Form Factor System
COM Express Module
Untitled-1 1 9/15/14 8:58 AM
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Silicon
10 Open source MEMS initiative seeks
to reduce barriers to sensor development Interview with Steve Whalley, MEMS Industry Group (MIG)
Software
12 Balancing power and performance in wearables
By Becky Oh and Andrew Taylor, PNI Sensor Corporation
16 Global Internet governance and the IoT
By Curt Schwaderer, Editorial Director
18 When one cyberattack becomes a thousand:
Protecting the IoTBy Ken McLaurin, Red Hat Inc.
Strategies
21 Can connected cars be secure cars?
By Kristen Maglia, Rogue Wave Software
24 Updating car software: Why delta technology is better than compression By Yoram Berholtz, Red Bend Software
26 Sensor-enabled nodes support the IoT for smart buildings and smart transportBy Roger Grace, Roger Grace Associates, and Alessandro Bassi, Alessandro Bassi Consulting
Special Features
31 Internet of Things
Special Section
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Connecting devices to the Internet of Things with Wi-FiBy Nikos Vokas, Econais
Encryption 101: Choosing the right scheme By Paul Dillien, Algotronix Ltd.
Departments
5 Tracking Trends
Rory Dear, Technical Contributor
IoT: Revolutionising home energy management
7 IoT Insider
Brandon Lewis, Assistant Managing Editor
Deconstructing the hype machine: Data analytics key differentiator for IoT
8 DIY Corner
Monique DeVoe, Managing Editor
IoT DIY with Bluetooth Low Energy and Arduino
9 Research Review
Monique DeVoe, Managing Editor
Building the clouds of the future
36 Editor's Choice 38
Web Wire
FEBRUARY 2015VOLUME 13
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4 Embedded Computing Design | February 2015
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31
IoT: Revolutionising home energy managementBy Rory Dear, Technical Contributor [email protected]
We’re privileged to live in an era that is truly heralding a revo-lution in the way we can take ownership of our home’s energy consumption. Of course a key driver is the spiraling cost of energy and focus on our own environmental impact and carbon footprint – but this isn’t purely a cost cutting exercise, this rev-olution also promises a substantial functionality increase that simplifies our ever-hectic lives.
Today, most homes’ energy management capabilities con-sist of appliance standby modes and CT based “per home” amperage monitors. Both technologies, whilst offering some benefit, have inherent flaws that don’t quite make the grade – enter the smart, connected home.
Let’s start with energy efficiency opportunities. The obvious function and the first we’re seeing hitting the UK market is “smart boiler” control. Functions available today are predom-inantly manual control via smartphones, be that within the home or remotely.
The next generation will see the introduction of habit learning intelligence, reviewing for example your daily hot water usage statistics, adjusting boiler activation times and dura-tion accordingly to reduce wasted energy. Let’s face it, I’m sure all of us would admit we purposefully over specify this “to be safe” and invariably have plenty of wasted hot water remaining at the end of each day as a result. We should also expect to see cross device integration, for example setting your burglar alarm when leaving the house automatically deactivates any active central heating – and any individual appliances that clearly offer no benefit remaining powered within an empty house.
Appliances are already following suit in “self” management. For those enjoying a hot drink as they wake, expect to see coffee machines and kettles activated by the deactivation of your smartphone alarm.
An environmental group calculated 1/3 ($2 billion) of lighting in the U.S. is wasted each year. “Smart lighting” offers not only the PIR type activation many of us are used to in our offices, but also the ability to configure individual lights’ brightness and activation times, monitor status remotely, and deactivate all lighting in an “empty home” scenario.
Now for user functionality improvements. Having recently become a first-time father myself, monitoring a baby can
consist of paranoid listening or gazing at a baby monitor, then conceding I’d better physically check just to be sure!
I want to instantly see environmental information such as tem-perature from my smartphone and don’t require a constant AV stream of every murmur falsely demanding my attention, an intelligent alarm would be infinitely better. Interestingly such advances are equally attractive to those caring for the elderly, increasingly wanting to stay in situ rather than seek residential care in their twilight years.
With the advent of online shopping and smart fridges, once the food packaging industry introduces RFID tagging your fridge can actively monitor “best before” dates and even automatically re-order essentials that are no longer detected.
What’s in this for the energy companies? Paradoxically, it may seem, those profiting most from soaring bills are heavily driving this revolution. Worldwide governments are applying pressure to these conglomerates to reduce household bills either by lowing the price per, or quantity of, kWh – the latter costing the energy company far less.
It’s also true that as energy bills soar, the levels of payment default do too, which negatively affects cash flow. Pressure on reducing carbon footprints internationally also drives future taxation levels for energy companies, another key consideration.
What risks are suppressing this innovation? As with most tech-nological revolutions the infrastructure costs are high; a typical homeowner will not encompass this cost alone as a business can usually provide a better ROI case due to significantly higher sav-ings – though as we’ve seen already a keenness exists from the energy companies to support funding this.
Ease of installation is another challenge, particularly when per-haps less technologically savvy householders find themselves at the front end. Securing any cloud-based remote access, as always, demands “security” high up on the agenda too.
The cross platform support of Wi-Fi and web servers is obvi-ously critical, though I worry, as per the HD-DVD/Blu-ray type wars of the past, that those major players are again deriving their own proprietary formats. From a business perspective these players are understandably aiming to secure market share, though that’s unfortunate for innovation and technology – a frustrating obstacle indeed.
TRACKING TRENDS
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11 ACCES I/O Products, Inc. — USB embedded I/O solutions: Rugged, industrial strength USB
2 American Portwell Technology — Portwell empowers intelligent solutions
19 Anaren — Join the evolution
35 Bluegiga Technologies, Inc. — Bluetooth modules
37 BZ Media - Wearables TechCon — Learn how to design, build and develop apps for the wearable technology revolution
15 COMMELL Systems Corporation — Intel Celeron J1900, N2930 and Atom E3845 SBC
27 Datalight — Driven to preserve and protect critical data for the lifespan of your automotive design
31 Datalight — Industrial IoT devices demand enduring, decision-quality data
34 Datalight — Revenue-grade data for industrial Internet of Things devices
28 Digital Voice Systems, Inc. — New AMBE+2 Vocoder chip delivers high quality voice at low cost
3 Embedded World — The gathering of the embedded community
32 Kontron — Hyperconnecting the Internet of Things
35 Kontron — IoT ready KBOX A-201
17 Micro Digital, Inc. — SMX RTOS is IoT ready
39 Mobile World Congress — The edge of innovation
35 Pocket Soft, Inc. — RTPatch: Binary diff patch software solution
29 Rogue Wave Software — Can you quickly find the code defect?
34 Rogue Wave Software — Deliver safe, secure mission critical software, faster
27 Security Innovation — Security Innovation ACE Labs
34 Toradex — Experience the difference between community support and committed support
33 Vitesse Semiconductor Corp. — IoT security done right
40 WinSystems, Inc. — Thinking beyond the board
6 Embedded Computing Design | February 2015
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Deconstructing the hype machine: Data analytics key differentiator for IoT
By Brandon Lewis, Assistant Managing Editor [email protected]
When I pulled up a chair next to Gartner’s Paul O’Donovan at the 2015 International CES earlier this year, one of the first things he said to me was, “You know what really angers me, Brandon? When companies add a Wi-Fi chip to a washing machine and claim it’s an Internet of Things device. That’s not the IoT.”
By now I’m sure you’ve heard reports about the IoT hitting the top of the “hype cycle,” as well as the projections that IoT services alone are projected to generate in the neighborhood of $260 billion a year by 2020. But as Paul rightly points out, much of the buzz surrounding the IoT hype machine to date has centered around adding con-nectivity to previously “dumb” devices, rather than focusing on the data pro-cessing and analytics that will actually provide intelligence to those devices and make the IoT truly transformative. For instance, while a washing machine you can run remotely is cool, lever-aging analytics about a washer that is running outside normal operating limits and diagnosing a problem with the machine’s motor can save you time, a huge mess, and open up additional service-based revenue streams for man-ufacturers; a smart home that informs you of power consumption is great, but a smart home that tracks usage patterns over time and adjusts the run cycles of your appliances to off-peak hours is a game changer that saves you money and presents utilities with the opportunity to tweak service plans. So why isn’t more attention being paid to data analytics?
Big Data structures and IoT analyticsOutside of the large investment in backend infrastructure required to get a data processing system off the ground, one of the major problems for Big Data analysis in the IoT is that data from dif-ferent sensors is often generated in different formats. The reason for this is that developers of the initial data logging infrastructure didn’t put much thought into formatting the logs of data producers (such as sensor devices) because humans were the primary consumers of log data. For us, parsing through different logs and extracting information from them isn’t much of a challenge, so loosely structured log for-mats sufficed.
But today, humans are not the foremost consumers of log data, not even by a long shot. We now increasingly rely on machines to perform the bulk of the processing and analysis on data gen-erated by other machines, and, unfor-tunately, machines aren’t as adept as humans at parsing through the diverse, semi-structured data sets associated with the IoT.
Recently, however, there have been efforts in the data science community to fix this data log illiteracy, notably through the open source Fluentd project (www.fluentd.org). Fluentd is a data collection software that attempts to reconcile the log formats of data sources with those of the backend systems responsible for processing and analysis. It is able to achieve this through what is called a Unified Logging
Layer interface, which restructures data logs from both the source and destina-tion in JSON format. Combined with a set of community-contributed plugins that make Fluentd compatible with numerous data sources and outputs, the Unified Logging Layer provides a mechanism for quickly collecting, fil-tering, and outputting log data from various inputs into a consistent schema that is suitable for analysis.
Treasure Data, Inc. (treasuredata.com) has been a major contributor to the Fluentd project, and uses a commercial version, the Treasure Agent, as part of its Big Data solutions. Using the Treasure Agent, the company can capture data logs from a wide range of sources in the IoT, telecom, retail, and advertising sectors before securely storing it in a cloud backend, from which clients can run SQL queries. In addition, business intelligence can also be integrated to automate massive IoT deployments and create new business opportunities, such as with the Pioneer telematics service currently under development (see opsy.st/TreasureDataFig).
Deconstructing the hype machineDiscussions around connectivity are important, especially as we continue to roll out the IoT infrastructure rollout. But that being said, there’s a clear difference between a “connected” device and an IoT device, and the dif-ferentiator is data analytics. Before the hype machine moves any further, I hope that becomes more central to the conversation.
IoT INSIDER
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IoT DIY with Bluetooth Low Energy and Arduino
By Monique DeVoe, Managing Editor [email protected]
Connecting yourself into the Internet of Things (IoT) is becoming increasingly accessible as DIY platform features and capabilities expand. DIY board and peripheral developers are coming out with more connected products all the time. Bluetooth Smart is one connectivity technology that shows a lot of promise for the IoT and small, low-power maker projects – plus the ubiquity of Bluetooth-enabled devices doesn’t hurt.
Bluetooth Low Energy (BLE) includes additional functionality on a Classic Bluetooth controller, including lower power consumption, AES-128 encryption using CCM for strong packet encryption and authentication, and extended range from 30 feet to 200 feet – good for home-wide automation and sensing projects.
RedBearLab (www.redbearlab.com) is a maker board company who was an early adopter to BLE on maker platforms, specifi-cally Arduino. The company focuses on IoT applications with special interests in embedded to mobile/portable devices and embedded to embedded technologies utilizing BLE and/or Wi-Fi. In 2012 they launched their first BLE shield for Arduino.
“At the time, there was a lot of interest in trying out the latest Bluetooth technology, but no ‘user-friendly’ development option was available – most of the BLE development tools still required very low-level embedded programming skills,” says Ma Chi Hung, CEO at RedBearLab.
For Apple product support, BLE was a great addition to a mak-er’s connected device development options.
“Before the launch of BLE, developing hardware that could work with iOS was limited to Apple’s Made for iPod (MFi) licensees,” Ma says. “Although you could use Wi-Fi instead of BLE, BLE is cheaper and more power efficient.”
The biggest advantages of BLE are its low energy consumption compared to Wi-Fi, and its better mobile device and PC sup-port compared to ZigBee, Ma says.
BLE does have some drawbacks as well: Support on Android and other mobile and desktop OSs are still under development, Ma says, among other issues. For example, before BLE v4.2, BLE couldn’t connect to TCP/IP networking directly, limiting its IoT usefulness. Even though that issue has been addressed, it’ll take time for the specification to become widely adopted.
“Bluetooth Low Energy was only introduced in 2010 – it is still evolving; it took classic Bluetooth more than 10 years before it became stable and mature,” Ma says.
In all, BLE excels at certain applications and struggles with others. RedBearLab sees a mix of all existing and upcoming connectivity technologies being the most useful in the future IoT space.
As for Arduino as an IoT platform, RedBearLab finds it to be a user-friendly, widely used platform.
“A lot of existing users are familiar with Arduino and there is a big community of Arduino users sharing their BLE projects online,” Ma says.
Arduino boards will celebrate their 10th year in 2015 – plenty of time to build a strong community and project resources. On the arduino.cc forums, “Home Automation and Networked Objects” is one of the largest topical boards (second to robotics at the time of posting – it’s hard to beat robots in project cool-ness), not to mention the various other communities that focus on the platform.
However, Ma says the Arduino’s Atmel MCU could case some scalability issues for BLE projects – running the library for BLE on the Arduino takes up a lot of resources quickly. Arduino can also be less than ideal for low power processing as it lacks a stand-by mode, but this could be addressed in future board versions.
Developing firmware can be a challenge based on your skill level. RedBearLab tries to make this more accessible to makers familiar with the Arduino IDE with their open source Arduino library for Nordic nRF51822 IC (github.com/RedBearLab/nRF51822-Arduino), an ARM-M0 SoC with BLE capability. More advanced users can still use KEIL, GCC, or mbed.org.
With a maker board, some development skills, and good commu-nity support, you could be on your way to the next big IoT thing.
“We believe that DIYers and makers are the driving force for the adoption as well as innovation in the IoT space,” Ma says. “The majority of IoT successes so far are from new startups with strong maker, open source, and crowd-sourcing back-grounds.”
DIY CORNER
8 Embedded Computing Design | February 2015
Building the clouds of the futureBy Monique DeVoe, Managing Editor [email protected]
The cloud has been a great addition to computing – bringing many benefits with its added computing power – but it still has a lot of room for improvement. The ability to make discoveries about and advance the cloud is difficult for typical cloud users, especially when system details such as network topologies and storage system design are intention-ally hidden from users. National Science Foundation (NSF)-funded CloudLab (www.cloudlab.us) aims to allow researchers to build their own clouds to make discoveries about cloud architec-ture and potential new applications.
“The goal of building the CloudLab infra-structure is to enable researchers to do transformative science on the architec-ture and applications of cloud computing
– to look at the clouds that we have now, and to think about how we can change them at fundamental levels,” says Robert Ricci, Research Assistant Professor, School of Computing at the University of Utah, which is leading the CloudLab project. “To do that work, you need to not just work within the cloud, you need to be able to control and instrument it at very low levels, and you need to be able to do that at a reasonably large scale.”
Ricci cites a few current challenges among many that hold the cloud back: security and privacy, predictability and real-time performance, and power effi-ciency. Encrypting data is a start, but there’s a long way still to go before cloud users’ data and the data col-lected about them can be considered truly private and secure. The ability to isolate cloud tenants’ performance isn’t perfect yet either, and the isolation and virtualization layers typically used add overheads and introduce hard-to-pre-dict performance variability. And as with many computing areas, power efficiency, integrating variable power sources like solar, and addressing cooling issues present many challenges.
These challenges are part of what CloudLab is set up to help researchers address by providing a tool to build clouds with maximum flexibility. Researchers have access to CloudLab’s hardware and software stack configu-ration components to get their custom clouds up and running in about 10 min-utes. Hardware includes typical x86-based servers in addition to hardware like ARM-based servers and OpenFlow switches that may have an impact on future cloud development. A fully programmable Layer 2 (L2) network between data centers is provided
through national research and educa-tion network Internet2. Popular soft-ware stack profiles are available, such as pre-built installations of OpenStack and Hadoop. If they choose, researchers can use these pre-built stacks, build their own, or use bare metal. Users have full control and visibility and don’t have to share resources with other users.
Three universities are hosting server clus-ters designed to handle different cloud computing challenges. The University of Utah’s server-class 64-bit ARM cores, built in partnership with HP on its Moonshot platform, emphasize power-efficient computing (Figure 1). Next to be built are the University of Wisconsin-Madison and Clemson University clusters, emphasizing high bisection bandwidth/storage and high memory, respectively. Current plans call for the system to grow to around 15,000 cores. Additions will include rolling out bare metal access to network resources and providing special-ized hardware such as FPGAs and spe-cialized switching equipment.
The project is poised to give current and future engineers a head start in revolu-tionizing cloud technology, as it is free for use by research and education com-munities. Ricci says it’ll help level the playing field across all institution types and sizes. The tool will be available for teaching classes, and in this role provide students with access to a level of hands-on experience that’s hard to come by.
Ricci hopes CloudLab can be as transfor-mative as the cloud itself.
“The cloud has been transformative because it has taken infrastructure that used to be time-consuming and expen-sive to produce and install, and made it easy for anyone to get it with almost zero effort and time,” Ricci says. “CloudLab aims to do the same for the cloud itself; that is, in CloudLab it’s as easy to build your own cloud as it is to set up a virtual machine in a traditional cloud. We hope that will similarly inspire people to come up with bold ideas about what the future of the cloud itself can be.”
RESEARCH REVIEW
www.embedded-computing.com 9
The University of Utah’s Downtown Data Center. Photo by Chris Coleman, School of Computing, University of Utah.
Figure 1
MEMS
Q What are the biggest challenges in sensor development, be it a single sensor or handling sensor fusion?
A few months ago I did a kind of MEMS 101 class with a bunch of startups, sort of an incubator unit out in Chandler, Ariz., and they had some very basic questions. One of them was, “Where can I get an accelerometer? Where do I buy one?” So it’s simple things like that. You can go to the MEMS site – the MEMS Industry Group (MIG) is a good place to start to get some resources. Then it’s going to the vendor sites like Freescale, ST Microelectronics, Bosch, etc., and then you start to understand what you need for your particular application. That’s the sensor side, picking a magnetometer, a gyroscope, or an accelerometer.
Then it comes down to how do I really bring these things to life by fusing the data that comes from them together with multiple sensors? That’s sensor fusion. Those are the algorithms that if you have a pedometer or a sleep analysis application that lets you know
if you’re walking or running or sitting to understand the different states you’re in.
The algorithms are essentially 80 percent math and working out the equations of what you need to do when things start
to move, and the other 20 percent is getting it to work in a real system. It’s the 80/20 rule – sometimes that last 20 percent can take 80 percent of the time – because what you’re doing is taking something that might work in iso-lation because of the mathematics of the algorithm, but when you put it in a fairly
harsh environment like a smartphone or a tablet, you’ve got a lot of other inter-actions going on with other electromag-netic forces. You’ve got speakers and magnets around, you’ve got the traces on the circuit boards that affect fields,
and so on. That all starts to get fairly complicated if you haven’t done it before. It’s not so much writing your first algorithm as it is getting it to work in a real system.
It’s possible to get these algo-rithms from algorithm com-panies, and there used to be quite a few, but they’ve all been swallowed up now by hardware companies. So there are no longer independent algorithm companies except for the likes of PNI in Santa Rosa, Calif., and Hillcrest Labs in the Midwest. You can obvi-
ously go to the hardware companies and they will license the algorithms to you, but one of the things I wanted to do with this open-source algorithm initiative, or what we call the Accelerated Innovation Community (AIC), was give these startup companies a foundation they could start from. Basically open-source, free software
Open source MEMS initiative seeks to reduce barriers to
sensor development
Whether working with a single input or fusing data from multiple
sources, getting sensors to work in real-world systems can be a
daunting task for the inexperienced. Steve Whalley, Chief Strategy
Officer, MEMS Industry Group (MIG) discusses some of the challenges
of sensor development and explains how MIG’s newly formed
Accelerated Innovation Community (AIC) is amassing industry expertise
to empower the next generation of sensor-enabled applications.
Steve Whalley Chief Strategy Officer MEMS
Industry Group (MIG)
10 Embedded Computing Design | February 2015
“What if we could do the basic stuff just to get people
going?”
algorithms that allowed them to get their first product going, even if it only got them a prototype or a proof of concept design that they could get in front of an angel investor just to give them a demo. What we’re trying to do is rely on some of the expertise of the people who have gone before us and worked on these kinds of applications and usage models and environments for many years and have tweaked those algorithms to get you started.
Q How did the AIC come about, and what is currently available to developers?
I actually started these discussions with Freescale over lunch, and they were willing to put in their basic algorithms. These are algorithms that probably most of the vendors have and they’ve all done their own version of them, and when a startup came along before the AIC they could try to license them for a cost or try to develop them themselves – for a basic pedometer, a step counter some, basic filters, whatever.
What we discussed was that people are reinventing the wheel every time for this very basic stuff, and it impacts cost, it impacts time to market, and we said, “What if we could do the basic stuff just to get people going?” That would allow them to focus more on their value add – on what the product is really about. Like on a smartphone, you’ve got to have something that does portrait landscape as you flip the phone around, but your real value add is then adding health applications or environ-mental monitoring applications. If I’m a startup, that’s where I want to focus. That’s how the AIC was born.
Freescale was the first to put their algorithms in, PNI has put some in, we’re getting algorithms from some of the universities like UC Berkeley and Carnegie Mellon, Analog Devices is going to be putting algorithms up there, and Kionix as well. Those are the main companies we launched with back at MEMS Executive Congress, and there are more coming aboard. There are some things up there, from a sensor fusion point of view, such as 3-axis, 6-axis, and 9-axis sensor fusion. So a design that uses basic inertial sensors
such as an accelerometer, gyroscope, or magnetometer could make very good use of them. There are also some basic filters like Kalman filters, Quaternion filters, etc., and PNI has put up some heart rate monitoring capability and a step counter as well.
This is not to try and take business away from the algorithm companies. Essentially, they don’t really get paid for these low-level algorithms – an OEM like Samsung or Apple isn’t going to pay for a basic step counter, they want the algo-rithm companies to focus on more of the complex, differentiated algorithms.
What the end user has now is a choice: you can take some very basic stuff and get started, and then either build on top of that in house or go license it from one of the sensor vendors or algorithm vendors that are still out there. So it’s giving you a little bit more choice.
MEMS Industry Group (MIG) memsindustrygroup.site-ym.com/ ?AIC @MEMSgroup opsy.st/MEMSIndustryGroupLinkedIn youtube.com/user/
MEMSindustryGroup
www.embedded-computing.com 11
Balancing power and performance in wearables By Becky Oh and Andrew Taylor
In consumer products, replacing or recharging a battery isn’t a
mission-critical operation. It’s just an annoyance. If that’s the case,
why is everyone so focused on power and cost for wearables and
IoT devices? One reason is that today’s wearables/IoT devices hold
marginal benefit for consumers, at least relative to the product price.
So component suppliers feel pressured to drive down costs while
improving the performance and power consumption of their parts.
Today most wearables rely solely on accel-erometers for activity measurements. But the problem is that all accelerometer-only based wearables do not deliver the same results. I put this to the test last year when I wore both Jawbone UP and Fitbit simul-taneously in order to compare the data.
What’s up with Jawbone UP and Fitbit?When I compared Jawbone UP and Fitbit, I found that both provided a solid over-view of my daily activities and largely reported the same activity trends. While I did get a detailed breakdown on number of steps, distance traveled, and calories burned, I didn’t feel all that enlightened about my daily activity levels. What’s more, I was puzzled that the data from two devices were off by 10-20 percent.
Discrepancy demystifiedFrom a technical perspective, the dis-crepancy between the two devices was not surprising since both Jawbone UP and Fitbit are accelerometer-only based devices, and each company uses their own algorithms to determine step count and intensity.
Accelerometers measure acceleration, and in a simple implementation, by set-ting a threshold trigger on the accel-erometer reading, one can extract the number of steps. Hence, most acceler-ometer-only based systems can be easily spoofed. Shake an accelerometer-based wearable device with periodicity, and it will pick up false positive steps and soft steps, which register below the set accelerometer threshold and may not be picked up. This causes either too few or too many steps to be counted.
Today, every manufacturer’s acceler-ometers are essentially the same. It is actually the performance of the manu-facturer’s algorithms that determine how wearables capture data. Clever algorithms can be developed to achieve higher-accuracy accelerometer-only step counting. PNI developed accel-erometer-only based step counting algorithms optimizing both power and
MEMS
12 Embedded Computing Design | February 2015
Jawbone Up and Fitbit dashboards for January 4, 2015.Figure 1
performance. This algorithm applies both biomechanical and heuristics-based filtering on threshold crossing features extracted over a 4-deep step buffer to accurately identify false or missing steps. In extracting the number of steps, the accelerometer-only algorithms proved to be more than 98 percent accurate while consuming less than 60 µA.
Testing algorithms for accuracyIn order to test the accuracy of the algorithms, we used 194 test vectors — including Brajdic’s “unconstrained smart-phone“ open source data[1][2], which include both slow and fast walking pro-files in each file — as well as data captured by PNI, including 30+ minutes of driving data with zero steps. The total log time was 305.25 minutes with 16,726 truth steps. Our algorithm reported 16,770 step counts resulting in a step count accuracy of 100.26 percent. The algorithm pro-duced less than 3 percent false positive (additional false steps – noted as Fp) and less than 0.5 percent false nega-tive (missed steps – noted as Fn), with a resulting median error of 1.46 percent. The distribution of Fp and Fn are shown in Figures 2 and 3. 90.2 percent of the test vectors had 1 Fn or less while 73.7 per-cent had 2 Fp or less (Table 2).
The step counting algorithm is pro-cessed in the SENtral coprocessor, and the total average power consumption — including the 3-axis accelerometer — was less than 60 µA, which is equivalent to 17,000 hours on an alkaline AAA bat-tery. These results look very good, and seem more than sufficient as a pedometer.
The power-cost questionKnowing that consumer products such as wearables are in cost-sensitive markets, is it worth it to include additional sensors even if it increases power consumption and cost? If a device is over $100, requires set-up, and needs to be charged once a week, I would want it to be more than just a pedometer. As long as it can maintain an acceptable power-consumption level and cost about the same as an acceler-ometer-only product, adding more sen-sors and functionality makes good sense. With MEMS gyroscopes (gyros) prolifer-ating in smartphones, making them small, reasonably low power, and affordable, adding a gyro to a wearable could be an ideal solution.
Hacked phone timePNI’s accelerometer-only step counting algorithm outputs step frequency, which the user can use in combination with leg length to relate the step count to step distance. However, adding a gyro input to the sensor fusion algorithm is an even better solution. It allows for accurate dis-tance traveled without user input (calibra-tion) and reduces false and missed steps.
That’s because the gyro lets us accurately maintain both the instantaneous and long-term Earth frame reference for gravi-tational and linear accelerations.
We wanted to put the gyro addition to the test so we took two Nexus 5 phones and modified the hardware to include PNI’s M&M modules, which include a SENtral coprocessor running motion
www.embedded-computing.com 13
January 4 Jawbone UP Fitbit Delta
Steps 18,362 22,0113,649
(16.6 percent)
Miles 8.7 miles 9.52 miles0.82 miles
(8.6 percent)
Total Calorie burn 1,792 cals 2,304 cals 512 (22 percent)
January 6
Steps 14,978 14,803 175 (1 percent)
Miles 7.28 miles 6.63 miles0.65 miles
(9.8 percent)
Total Calorie burn 1,698 cals 1,505 cals193
(12.8 percent)
Data comparison between Jawbone UP and Fitbit.Table 1
Total Files 194
Total Steps 16770
Total Truth 16726
Total Fp 488
Total Fn 87
Total log time (minutes) 305.26
% Accuracy 100.26
% Median Error 1.46%
% 0 Fp 42.78%
% 0 Fn 70.10%
% 1 or less Fp 61.86%
% 1 or less Fn 90.21%
% 2 or less Fp 73.71%
% 2 or less Fn 97.94%
Mean F1 score 98.30%
Mean Recall 99.43%
Mean Precision 97.30%
Latency 3 steps
Summary of algorithm results for 194 test vectors.Table 2
sensor fusion algorithms, and inertial sensors from either ST or Bosch and AKM. Although the Nexus phones have gyros, accelerometers, and mag-netic sensors, we needed to hack the phone to include the M&M modules so we could easily control the sensors
in Android and run low-power step counting algorithms from SENtral. We used two Nexus 5 phones, one with accelerometer-only step counting algorithms and the other with an accelerometer- and gyroscope-based pedestrian dead reckoning (PDR)
algorithms. Holding these two phones on top of each other, we went around a test bench in the lab multiple times, walking 101 steps.
Figure 4 shows the result after 101 steps. It is interesting to note that both algo-rithms report 101 steps, but the device to the right running PDR algorithms — using both a gyroscope and acceler-ometer — reported distance traveled without having to calibrate or input the users stride length. It was also able to trace the user’s path of travel.
As we know from earlier tests, an acceler-ometer-only based system has limitations. It cannot track the user’s path of travel and cannot automatically calculate dis-tance traveled unless the user inputs their average stride length. And using average stride length to calculate distance trav-eled is not as accurate as measuring the distance traveled for each step via a gyro-scope with sensor fusion algorithms.
Worth the investmentAdding a gyro to a wearable device is a logical choice. The results from an accu-rate PDR algorithm could allow us to create more compelling wearable appli-cations, such as tracking lost children in a mall or monitoring elders. That’s more compelling than mere activity moni-toring, for example, and it’s just the tip of the iceberg as to where these applica-tions will ultimately go.
It’s true that there are additional costs and power to consider. The incremental bill of materials (BOM) cost to add a gyroscope would be $1-$2 for the gyro and another $1 for added processing. The increase in power would be an additional 1-2 mA for the gyro and about 400 µA to run the PDR algorithm. That’s just $2-$3 in incre-mental hardware costs.
While the increased system power is more than 20 times that of an accelerom-eter-only based step counter, the total system would run for about 12 hours. By opening up new classes of applica-tions to wearables, that’s a trade-off I am willing to make. Manufacturers looking for that competitive edge in a fast-moving marketplace will see it the same
SILICOn MEMS
14 Embedded Computing Design | February 2015
Anderson-Darling Normality TestA-Squared 22.68P-Value < .0005
Mean 2.5155StDev 4.0684Variance 16.5516Skewness 2.38929Kurtosis 6.21937N 194
Minimum 0.00001st Quartile 0.0000Median 1.00003rd Quartile 3.0000Maximum 21.0000
95% Confidence Interval for Mean 1.9394 3.091695% Confidence Interval for Median 0.8685 1.000095% Confidence Interval for StDev 3.6998 4.5191
Anderson-Darling Normality TestA-Squared 31.16P-Value < .0005
Mean 0.44845StDev 0.86971Variance 0.75640Skewness 3.0011Kurtosis 12.6153N 194
Minimum 0.00001st Quartile 0.0000Median 0.00003rd Quartile 0.0000Maximum 6.0000
95% Confidence Interval for Mean 0.32530 0.5716195% Confidence Interval for Median 0.0000 0.000095% Confidence Interval for StDev 0.79093 0.96607
False positives for 194 test vectors.
False negatives for 194 test vectors.
Figure 2
Figure 3
way. If adding a gyro requires only incre-mental costs/power consumption, but brings them vast numbers of new cus-tomers, then gyro- and accelerometer-based wearables are in our near future.
References[1] Brajdic, Agata, and Robert Harle. “Walk detection and step counting on unconstrained smartphones.” In Proceedings of the 2013 ACM International Joint Conference on Pervasive and ubiquitous computing, 2013, pp. 225-234. [2] www.cl.cam.ac.uk/~ab818/ubicomp2013.html
Becky Oh is CEO, Precision Navigation Corporation, and board member at PNI Sensor Corporation.
Andrew Taylor is Vice President of Engineering at PNI Sensor Corporation.
PNI Sensor Corporation www.pnicorp.com www.linkedin.com/companies/7561 www.youtube.com/user/pnicorp
www.embedded-computing.com 15
Nexus phone on the left has accelerometer-only based step counting and Nexus phone on the right has accelerometer- and gyroscope-based pedestrian dead reckoning (PDR).Figure 4
NewsMEMS Industry Group announces first open-source algorithm communityBy MEMS Industry Group opsy.st/MEMSAlgorithmCommunity
BlogMy Internet of Things 2015 wish listBy Adam Justice, Grid Connect opsy.st/2015IoTWishlist
E-cast Make sense of it all – Discover wearable patches with secure, contactless NFCPresented by Texas Instruments ecast.opensystemsmedia.com/517
More on… Sensors and IoT
Global Internet governance and the IoTBy Curt Schwaderer, Editorial Director [email protected]
Many consider the Internet of Things (IoT) a revolution. If you’ve been in the embedded industry for any length of time, you probably consider it more of an evolution than revolution. Since the advent of the microprocessor, the embedded industry has been creating embedded systems in virtually every industry with an ever-increasing level of sophistication. Graphics, storage, analysis, and management are all things that have progressed within the embedded realm. And of course commu-nications between devices and systems has been happening in the embedded industry for well over 20 years.
As the Internet continues to mature, adding “on-ramp” technologies to embedded devices that enables
communication over the Internet all of a sudden makes that device a member of the IoT family. We embedded developers tend to ignore all but the technological impact of our creations and often assume use cases and market needs will drive the technology to a useful end result.
However, there are other forces at work. The Global Commission on Internet Governance (GCIG, www.ourinternet.org) has been hard at work looking at the impact of the Internet and examining various issues that affect Internet gover-nance. It is within the governance realm that all things Internet represent a revo-lution – there has been nothing like it to provide a basis of governance and the use cases and their implications have never before been seen.
If you’re an Internet purist, you may be rolling your eyes right now at the thought of the government getting involved in legislation pertaining to the Internet. However, there are a number of social implications including Internet access, interconnection and economic development, surveillance, cybercrime and threats, and even human rights.
For example, a recent global survey on Internet security and trust con-ducted by the Centre for International Governance Innovation (CIGI), 83 per-cent of users believe affordable access to the Internet should be a basic human right. There are people thinking about the impact of the Internet and its cor-responding access, security, and ethics implications.
Securing the Cloud
Prime Minister of Sweden and Chair of the Global Commission on Internet Governance (GCIG) Carl Bildt discusses ongoing work of the two-year initiative. Watch the video: opsy.st/GCIGCarlBildtPressConference
16 Embedded Computing Design | February 2015
By extension, IoT devices are not immune to the impact of Internet gov-ernance. These governance issues are not directly targeting IoT devices and applications, but many of the chal-lenges and issues being addressed have IoT implications.
Government organizationsCIGI (www.cigionline.org) is an indepen-dent nonpartisan think tank that collabo-rates with policy, business, and academic communities around the world.
The CIGI recently released a brief called “Finding Common Ground: Challenges and Opportunities in Internet Governance and Internet-related Policy” (www.cigionline.org/publications/common-ground). It’s a synopsis and commentary on the work of the GCIG. The GCIG was launched in January 2014 and has a two-year charter to produce a comprehensive stand on the future of multi-stakeholder Internet Governance.
The 64-page briefing book produced by CIGI provides a wide range of Internet-related governance topics such as addressing systematic risk and security issues, cybercrime and surveil-lance activities, protecting innovation, and governance between countries and jurisdictions relating to cloud com-puting, Big Data, and individual rights online. IoT feeds into all these topics, so the conclusions reached within the GCIG will impact IoT.
Internet governance concernsThe briefing book contains a lot of inter-esting challenges and opportunities relating to a wide variety of topics. While not explicitly called out, many could potentially relate to a wide variety of IoT and Industrial IoT applications. A few are discussed below:
õ Intellectual property – The main concern involves content providers and the increasing involvement of individuals utilizing copyrighted content within their “free” videos. This may relate to IoT environments where the information being transmitted involves user information that may be carrying copyrighted information. Are you responsible for identifying this?
õ Law enforcement cooperation – Network operators must comply with lawful intercept regulations to combat cybercrime and terrorist activity. As a company that provides an interconnected IoT environment, what if law enforcement requests information about specific users within your IoT system?
õ Traffic shaping – There are network operators that own network infrastructure that re-sell access and bandwidth to their networks. One form of monopolizing the network is allocating a lower level of service to specific service providers thereby giving a competitive advantage to those that pay more for higher bandwidth. What happens if networks interconnecting your IoT application don’t provide enough bandwidth for satisfactory operation? Do you have recourse?
õ Data sales – A huge motivating factor these days is Internet user network data access for marketing and sales purposes. IoT promises to provide a landslide of data about the users of these IoT
devices from geo-location to their online activities, perspectives, and preferences. As an IoT developer, how much information are you allowed to collect on the user of the application? What responsibilities do you have about protection or access of this information that could be used for sales and marketing purposes?
õ Tarrifs, jurisdiction – Internet services and interactions are global. Endpoint to endpoint and all the hops in between make services tariffs and jurisdiction challenging. Internet commerce may or may not be taxable. If it is, what are the tax implications for your IoT application?
Internet governance is a hot topic worldwide from security and eco-nomics to human rights and access. These uncharted waters will begin to take form over the next few years as global government regulators look at the issues and propose legislation to address them.
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When one cyberattack becomes a thousand: Protecting the IoTBy Ken McLaurin
It sounds like a scenario out of a sci-ence fiction thriller – in the far future, everything from traffic lights and rail switches to pacemakers and hospital monitors is connected, leading to an improved quality of life but putting every day citizens on the front lines of computer security. Not only are these devices connected, they are actively talking to each other – in fact, many are downright chatty! Instead of just stealing patient medical data or customer credit card data, security breaches and hacker attacks can cause widespread devastation, from traffic accidents to turning off critical medical devices. Scary, right? Now imagine that this connected future isn’t really that far off, thanks to the emergence of the Internet of Things (IoT), which means that security of smart devices is front and center today.
An IoT implementation is essentially a composite, distributed solution, meaning that it’s a set of applications deployed across several physical and logical servers. When you consider how this complexity interacts with security concerns, you begin to understand why security issues can very well end up lim-iting what enterprises get out of the IoT. Like any distributed solution, every environment and application has its own security requirements. Added to this is the challenge of securing the solution as a whole and addressing the issues resulting from its scale and the high degree of connectivity, which massively increases the attack surface and raises the stakes of what’s at risk.
There are two things that characterize today’s enterprise IoT solution: the data that’s flowing through the system and the degree to which devices and the data center connect and communicate to each other. Systems composed of devices relaying information to the data center and operational applications have been with us for decades, but today’s difference lies in how these devices func-tion. Where in earlier examples devices typically were passive data collectors, they now can operate in their environ-ment based on data that they’ve col-lected or that has been relayed to them from the data center. It’s essentially the difference between a thermometer that reads temperatures, passing that data along without acting on it, and a thermo-stat that’s part of a smart energy solution that can change a home’s heat, not only in response to local readings but based on readings from thousands of other thermostats aggregated into an energy utilization grid. By virtue of the device being connected to applications con-trolling energy infrastructure, however, it poses far more risk than when it was a passive data collector that could impact only a single home.
In the thermostat scenario, the likely goal of an attack would be to manipu-late some aspect of the energy grid by gaining access to the operational appli-cations. In other scenarios, the target of an attack could be the data itself. For example, devices used in financial transactions or health care carry per-sonal data protected by privacy regu-lations. The data flowing through an
IoT implementation must be protected both when it is “at rest” on a device or gateway and when “in-flight” during transmission among various tiers of the distributed architecture. This sheds light on the three security areas of the utmost importance to the IoT:
õ Hardening devices
õ Protecting data
õ Securing connections
Hardening the deviceVolumes can be written about pro-tecting the physical device from tam-pering, vandalism, and the elements. Securing the software on the device, however, is equally important as it serves as the entry point into the enter-prise system, the area where maximum damage can be done. Hardening the device software is a matter of protecting the data and the environment in which the applications on disk operate. One recommended approach is to use disk encryption and install a highly secure operating system. The disk encryp-tion protects the data itself while the security policies enforced at the oper-ating-system level will help ensure that applications are accessed only by privi-leged processes. Both layers of security are required to make sure that the device software cannot be compromised.
Deploying secure devices into the field is one thing – maintaining their security is another. Keeping the device software as secure as possible requires applying security patches as they become avail-able, a very different approach to how
Securing the Cloud
18 Embedded Computing Design | February 2015
most embedded devices are treated today. The “dumber” the device (the less functionality and lower cost it has), the greater the tendency to ignore it until it’s time to replace it. The sheer scale of an IoT deployment that can include tens of thousands of devices makes maintaining security a daunting proposition, but if the devices can be the entry point for an attack on enter-prise systems, you must include the ability to deliver patches to devices as part of your security strategy.
In highly regulated industries, managing patch delivery and security maintenance comes with an auditing requirement. In which case, you not only have to apply patches to thousands of devices, but you must be able to document and confirm that you took the appropriate steps to secure the devices. Include a management tool (or set of tools) as a project requirement to be able to effi-ciently push updates out to thousands of devices and report on the state of each device in terms of applied security patches and other software changes.
Securing the communicationsIt’s not just the devices that are vulnerable to attack. One common method cyber-criminals use is hijacking data midstream. Here again, you can apply security at various layers. You can encrypt the data, use secure networking protocols such as Transport Layer Security (TLS) running on a LAN/WAN and use VPN to further connect LANs over a WAN instead of relying on the Internet. Running a private network infrastructure over dedicated fibre rather than communicating over the Internet is a far more secure scenario, though an expensive one. Clearly, the cost and overhead of these methods has to be weighed against the risk.
There is another way to intercept device communications – posing as a trusted entity. It is essential that any inbound or outbound communication is verified as coming from or going to a trusted device or server, typically using authentication keys or certificates. Domain managers such as Microsoft Active Directory or the FreeIPA (identity, policy, and authentica-tion) controller in Linux provide this level
of security for applications and users and can be extended to manage security for IoT devices and processes.
Protecting the DataData encryption has been mentioned in terms of hardening the device by encrypting data written to disk and in terms of securing the communications among components. There has tradi-tionally been performance cost to data encryption, which is probably the reason why enterprises have taken shortcuts in this area – with dire consequences as breaches at Home Depot and Target have recently showcased. However, recent processors include dedicated hardware instructions for crypto accel-eration, making encryption much more feasible. Encryption need not be an all-or-nothing approach. Understanding the data that is being collected and trans-mitted in an IoT system and knowing what the security requirements are for protecting the data at rest and in flight are key to designing a pragmatic secu-rity architecture. As a rule of thumb, if data is valuable – either direct economic
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value or cost if it is exposed – it is worth the cost of encrypting it.
Not all data needs the same degree of protection. Sensor readings that have no real meaning without context or where little damage can be done if these are hijacked or compromised probably don’t have to be encrypted, or you could implement a simpler solu-tion like using a single crypto key for all devices. This makes the devices easier to deal with while providing some protection.
Save the encryption for data that must be protected due to its value, the potential exposure a leak could affect, or damage caused by tampering with a data stream. To go back to the home heating example, stealing or jumbling a home’s temperature readings is low impact while intercepting and manipu-lating temperature data that controls a biomedical lab’s HVAC system might result in significant damage.
The same approach to measuring risk and impact will guide decisions about how much protection is needed for data at rest, that is data written to disk on a device or server, and how much is needed when data moves between components.
In some instances, encryption is not enough so data is transmitted in ways that context is difficult to reconstruct if some of the packets are intercepted. For example, one can separate credit card numbers from identifying informa-tion and send them in different transmis-sions. Some organizations use algorithms for “jumbling” and re-assembling data streams in addition to encryption.
First stepsIs security for the IoT complex? Yes, because the attack surface is huge, the risk can be very high, and the conse-quences severe. The good news is that the tools at your disposal are familiar to most IT organizations and well proven. The challenging part is providing the right level of security at each device, gateway, or server and then surveying all the connection points, assessing the risk posed at each one, and choosing the best-suited protection method (Table 1).
Ken McLaurin is Senior Manager, Product Strategy at Red Hat Inc.
Red Hat Inc. www.redhat.com @RedHatNews linkedin.com/company/red-hat plus.google.com/+RedHat youtube.com/user/RedHatVideos
SoftwaRE Securing the Cloud
20 Embedded Computing Design | February 2015
Items Recommendation
System-wide
Plan for a full product lifecycle – design, deploy, maintain, update, retire, and replace. Achieve as much consistency as possible by addressing security at the lowest possible level of infrastructure: operating system, network protocols, disk.
DevicesDesign security and access policies for each device type or deployment environment.
Applications Follow authentication best practices.
Data setsDesign security policies for each type of data for various stations where data is at rest or in flight.
ConnectionsUse secure network infrastructure, a secure protocol, and encryption of data.
Guidelines for securing an Internet of Things solution.Table 1
BlogSecurity threats: The Dark Side of the IoTBy David Somo, ON Semiconductor opsy.st/IoTSecurityONSemiBlog
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More on… Security and the Cloud
Connected Cars
Can connected cars be secure cars? The growing concern over software security in the automobile industry By Kristen Maglia
Recent statistics about automobile safety are hard to miss these days. Attention-grabbing headlines have exploded both in main-stream and social media, and you can hardly read a blog without seeing one of them: “Hands-Free Driving is Not Trouble Free.” “Toyota Widens Recall of Cars with Takata Airbags.” “Hacked Driverless Cars Could Cause Chaos in London.”
As sensational as these headlines are, the concern is real. Technology is moving faster than the gov-ernment’s attempts to regulate, and nobody wants to stifle innovation, much less slow the consum-er’s access to more and better bells and whistles on their cars. Although it seems like an overnight development, automotive manufacturing has fol-lowed a long road of innovation since the dawn of the electro-mechanical era of the 1970s through to today. Only now we’re at a tipping point. Innovation no longer starts and ends with a car’s mechanical components; software has now taken over as the kingpin of the automobile industry, not because software in cars is a new development, but because of the sheer volume of code powering cars and the resulting complexity.
Estimates are that 60-70 percent of vehicle recalls are due to software glitches[1]. Cars are run by networks of computers, wireless connections, and electronic control units (ECU), offering the potential for hackers to access critical car controls such as steering and braking. Cars today also can easily connect to smart devices and the Internet, so it’s easy to see how those critical systems can be exposed. Exposed systems could mean scenarios including drivers losing control of cruise control mechanisms, braking systems, and other safety-critical operations.
So we’ve come to the “connected car.” While nebulous, this term is appropriate in describing this phenomenon. Most new cars coming off the production line today really are connected; they can easily communicate with other devices both inside and outside the vehicle. Smart devices sync to deliver in-car infotain-ment, to provide diagnostic information for the mechanic, and to
www.embedded-computing.com 21
enable extra convenience controls such as navigation, roadside assistance, and parking apps.
It’s not just new models either. Older cars are increasingly con-nected using new systems, like O2’s Car Connection solution, which links drivers to their cars via smartphones, providing diagnostic information directly to the phone and to tools like a vehicle finder.
So what controls the functionality in today’s cars? We’ve heard that today’s average high-end car has 100 million lines of software code[2], and anyone can appreciate the magnitude of that number, at least on the surface. (Especially when it’s contrasted with the space shuttle which, according to NASA, only contains 400,000 lines of code.[3]) But what does that number really mean? What does it mean to the consumer? To the automotive software supply chain?
It means that all of those millions of lines of code – regardless of where they come from – need to be bulletproof. Stakes are high. And, in vehicles, when software doesn’t work the way it’s intended, it’s serious.
The new role of the automobile manufacturer: Software security expertsThe business of keeping automotive software secure is a dicey one. Today’s connected car is assembled from pieces, parts, and code from various companies that make up the supply chain to the manufacturer, and the end result is what ultimately ends up on the showroom floor. For manufacturers with roots in mechanics, it’s increasingly difficult to get their processes up to date around the vastly different needs of hardware and software. The complexity that comes with the shift to the Internet of Things, devices, and communications networks is additive to existing processes and systems. Now, managers at car manufacturers need to ensure security within everything that makes up their cars. These same managers are also tasked with quickly adding the latest and greatest features to stay competitive.
Security often takes a back seat when financial pressure mounts. It begs the question: How much thought has actually gone into the software security of automobiles before they are released? Security has not always been part of the day-to-day workflow in the development world. Developers might not even know what they should be doing as individuals to ensure the code they’re writing does not have security problems. And, typical development team leads may have not implemented the proper software tools, education on standards, and how to comply and production processes to make the job of ensuring security seamless.
Manufacturers need to recognize that they are not only supplying cars, they are now cyber security managers as well. Although automobile hacks have yet to become commonplace, they do happen. Recently in Canada, authorities attributed “phantom” car break-ins to hacking, and found that a simple program could
be written in a matter of hours that jammed the message from the key fob to the car, disabling the locking system.[4]
Securing the supply chainFrom the computer screen to the assembly line, manufacturers should now consider themselves attack vectors who are respon-sible for everything that goes into their products, not just what’s directly within their own development groups.
It’s important to remember that the development process has evolved. Once a single developer or team of developers cre-ated code to solve a problem. Now, software development is very much akin to an art form, as developers assemble parts from various sources and skillfully coordinate their functions to create a cohesive, working product in the end.
For instance, a company provides a manufacturer with the software that controls airbags. Developers for the airbag com-pany may have incorporated open source software to visualize testing data, or they may have grabbed some prefab code to create reports. Some code controlling the airbag was written from scratch – but that could up as little as one percent of a total application. Another nine percent comes from the rest of the development team, and as much as 90 percent of any application could come from other sources – commercial software packages, outsourced development, open source, and legacy custom code. “It just doesn’t fly anymore to pass responsibility for security to another party – whether it’s the manufacturer to the supplier, or the supplier to the manu-facturer,” says Stephane Raynaud, automotive account liaison for Rogue Wave Software. “It makes sense to leverage pre-built functionality; every participant on the supply chain has to make sure every bit of it is safe and secure.”
Protecting companies and consumers: Know what’s in your code – all of it.How can companies protect themselves – their reputations, their financial stability, and their customers? They can do it by knowing, understanding, and taking responsibility for all of the code that makes up their product – not just what their own developers have written.
The automobile industry could take a page from the playbook of telecom companies who faced a similar challenge several years ago when their devices suddenly became the only thing standing between the consumer and complex, embedded software code. These companies learned quickly that they could not pass all of the responsibility to the companies that supply the features in their product. They also learned that their product was only as strong as their weakest sup-plier’s code.
The bottom line is that companies need to open the aperture of what they’re securing, and they need to do it before they become the subject of dramatic news headlines. And, those who are part of the supply chain need to tighten processes. Putting security first means three things:
22 Embedded Computing Design | February 2015
Strategies Connected Cars
1. PoliciesOrganizations need to implement policies to take the guess-work out of how to ensure the security of its code. Successful policies are easy to follow, easily accessible, and properly edu-cate the workforce so that developers know and understand security issues and how it is applies to their workflows.
Management should implement these two types of policies:
õ Operations policies – These are documented policies outlining the tools that are approved for use in an organization, the agreed upon processes, and testing practices and test suites – all of which are designed to ensure optimal code security. Typically these decisions and policies are managed by an enterprise architecture group.
õ Open source software policies – Designed to outline how an organization manages the open source in its code base, these policies cover how open source is used and when it is considered appropriate in the development process. More and more organizations are implementing groups within existing company functions to create and manage policies around open source code.
2. ProcessesClear processes are key to secure software development. Teams from both the automobile manufacturers and the companies within their supply chains need to agree that security processes are important, and then mandate consistent application as non-negotiable. Organizations can start by educating their own workforces on the importance of security and defining how each how each individual plays an important role in releasing secure products.
Though top-level management may direct the need for pro-cesses, front line development managers should deploy pro-cesses that bring security into developers’ existing workflows and manage them ongoing. Processes should be seamlessly integrated with builds to ensure important steps aren’t for-gotten, overlooked intentionally, or are too difficult to maintain. Processes should include:
õ Building automated test suites
õ Teaching secure coding practices
õ Putting processes in place for acquisition and monitoring of open source
õ Making tools readily available and updated regularly
And, anything developed by internal teams should apply to the supply chain. When accepting code from suppliers, manufac-turers have a right to ask what processes are in place, and even require contractually that clean practices be applied.
3. ToolsKnowledge goes a long way, but developers can only do so much to ensure secure code. Human error and hidden threats need advanced tools built that expose issues to the developer. Management should provide their development teams with automated, easy-to-use tools that operationalize policies and procedures. These tools should be built into processes, and automate the detection of critical security issues. Ease of use
will determine if they get used, and if used, can encourage good coding practices. Developers may have some fear about pro-cesses cutting into their creativity, so managers need to dem-onstrate how easy certain tools are to use, empowering them even more toward innovation. In short, providing the right tools means better, more secure software with less effort by the indi-vidual developer.
Development managers can help ensure secure software development:
õ Open source scanning and support – As open source has become a large component of virtually any application, the first step is to discover what and where OSS is across all code lines. Also, ask these questions: Can the OSS be supported during any failures? Which packages have security vulnerabilities? How can we better manage our OSS use?
õ Static code analysis – Static code analysis is the process of analyzing the health of source code without actually executing it. Developers should be able to identify and correct problems with code before it is ever checked in, saving time earlier in the development process.
õ Dynamic code analysis – As a complement to static code analysis, dynamic code analysis is the process of executing code in real time to find security errors while it is running. Developers in complex environments using extensive memory and compute resources should have a dynamic code analysis tool at their disposal to perform simultaneous debugging of many processes and threads at once.
Setting the bar higherAs cars become more connected, and our dependency on the software that powers them grows, the need for advanced tools to ensure security in code will grow too. Stand out organizations in the automotive industry will set the tone for other compa-nies by not only creating higher standards for their developers, but by demanding the same level of excellence from their entire software supply chain. Progressive development managers today are already taking steps to defend their companies against worst case scenarios by providing expert knowledge, policies, processes, and tools to their developer workforce.
References[1] http://www.automotiveworld.com/megatrends-articles/connected-cars-connected-era [2] http://www.motorauthority.com/news/1026505_modern-luxury-vehicles-claimed-to-feature-more-software-than-a-fighter-jet [3] http://www.nasa.gov/mission_p+ages/shuttle/flyout/flyfeature_shuttlecomputers.html [4] http://www.cbc.ca/player/News/Canada/Montreal/ID/2642436500
Kirsten Maglia is Automotive Campaign Director at Rogue Wave Software
Rogue Wave Software www.roguewave.com @roguewaveinc opsy.st/RogueWaveSoftwareGooglePlus linkedin.com/company/rogue-wave-software youtube.com/user/roguewavesoftware
www.embedded-computing.com 23
Updating car software: Why delta technology is better than compression By Yoram Berholtz
There is a lot of talk about soft-ware revolutionizing the automo-tive industry and the conversation is growing because of how soft-ware management will impact the whole business of recalls. The out-rageous amount of good money going after bad is the reason why car manufacturers and Tier 1 sup-pliers are looking for an optimized and alternative way to reduce the amount of time it takes to deliver a software update, reducing the cost associated with recalls and improving customer satisfaction. If the same method for performing automotive software updates in production, at the dealer, or at home continue, so will the inef-ficiencies that are causing car manufacturers to pay hundreds of millions of dollars every year.
Connected Cars
24 Embedded Computing Design | February 2015
250200150100
500
Total ProgrammingTime in Seconds
Full Download Compresion +Pipelining
V1-V2 Delta
-43%-71%
4,500,0004,000,0003,500,0003,000,0002,500,0002,000,0001,500,0001,000,000
500,0000
-37%
Full Image
Download Size in Bytes
Compressed V1-V2 Delta
-97%
-43%-71%
-37%
-97%
Download size and programming time comparison between a full file download, a compressed file, and using the delta updating method.Figure 1
When doing a software update either over-the-air or via a cable, one goal is to deliver the smallest update package possible, reducing update time and cost. There are several methods to reduce the update file size but the two most notable are compression and delta (differential) updates – only sending the code that is different between the old software that needs to be updated and the updated software.
With both technologies the goal is to reduce the number of bytes that are being delivered to:
õ Reduce the download time – The new software needs to quickly get to the car’s gateway (e.g., head-unit) in order to start the update process
õ Decrease the amount of needed memory – After the new version is delivered, there needs to be room to
store it before the update is started
õ Decrease the transport time between the gateway and the target ECU – In case of ECU update, the new version needs to go through the CAN/LIM/NOST bus, which is limited in bandwidth
õ Reduce the update time – The update time depends in some cases on the amount of changes that exist in the new version
There are tests conducted by leading automotive companies and scientific research that show in detail the compar-ison between compression solutions and delta update technologies.
Vector, an embedded software testing company, worked with Red Bend on a proof-of-concept testing the effi-ciency of the delta technology. Vector chose an NXP chipset that is common
in ECUs – such as the powertrain – and connected it to vFlash via the CAN bus. The vFlash functions as the off-board tester for managing the reflash process. Vector ran an ECU reflash three times – one with a software full image, one with a compressed image and the third with using Red Bend’s delta technology com-bined with Vector’s bootloader.
The efficiency of the delta technology is much greater than any compres-sion technology (LZ77 in this case) (Figure 1). Using compression, the file went from 4.1 MB to 2.5 MB. Using delta technology, the file went down to 128 KB. There are interesting results that also sup-port delta technology when comparing programming time associated with dif-ferent processes and technologies. For the full download, programming time was 215 seconds; compression and pipe-lining was 124 seconds; in comparison, a delta program time was 63 seconds.
Dr. Ralf Schmidgall in his thesis “Automotive Embedded Systems Software Reprogramming” (opsy.st/SchmidgallThesis) analyzed the methods of reducing the size of the version when doing software updates. In Table 1, Dr. Schmidgall summarizes the results of a theoretical case study to compare the approaches.
The delta technology results in a much smaller file than any method of compres-sion, and the impact on the update time is dramatic, even if the speed of the CAN bus is increased to 1000 Kbps also in this case the advantages of delta is clear.
In his summary Dr. Schmidgall wrote, “Differential file update provides the best theoretical results of all researched approaches ... If the increase of ECU soft-ware sizes continues in the future, this approach might be the only sustainable one to solve the problem of increasing reprogramming times” (Figure 2).
Yoram Berholtz is Director of Business Line Management at Red Bend Software.
Red Bend Software www.redbend.com @redbend linkedin.com/company/red-bend-software
www.embedded-computing.com 25
q CAN bus system todayq
- Protocol optimizations- Data size reduction(compression, partitioning etc.)w
- Network optimizations- Direct Ethernet access- Ethernet VCI-bus/backbone- FlexRay schedule optimization
e
-MRAM-Differential File Updater
Todayt t
ECUSoftware Size
Max. allowedprogramming time
w
r
e
As ECU software size increases, delta or differential updates can help address the challenge of increasing reprogramming times.Figure 1
DescriptionFile Size
(Data to transmit)
Data Transfer Time on CAN Unit
125 500 1000 Kbps
Original File (complete)
32 MB 4127.2 1031.8 515.9 s
Compression (-25%)
24 MB 3095.4 773.8 386.9 s
2 Partitions 16 MB 2063.6 515.9 257.9 s
Partitioning and Compression
12 MB 1547.7 386.9 193.5 s
Differential File 1 KB 0.1 0.031 0.016 s
Theoretical case study of file size reduction methods.Table 1
Sensor-enabled nodes support the IoT for smart buildings and smart transportBy Roger Grace, Roger Grace Associates, and Alessandro Bassi, Alessandro Bassi Consulting
The global Internet of Things (IoT) phe-nomenon is opening unparalleled opportu-nities for sensor technology. A presentation at the 2014 IDTechEx Conference claimed that the bill of materials (BOM) for an IoT node is split evenly between sensors and transceiver (at 45 percent each), with a small part left for the microprocessor (5 percent) and other functions (5 percent). Internet of Things numbers can make heads spin: Cisco IBSG predicts 25 billion IoT devices by 2015 and 50 billion by 2020;
Gartner Research values the aggregate number of IoT sensors to reach $10.1 billion by 2020 from $1.3 billion in 2014, with a com-pound annual growth rate (CAGR) of 41.7 percent. IDTechEx has estimated the market value for IoT IP-addressed sensing nodes to grow from less than $1 billion in 2015 to greater than $48 billion by 2025 (Figure 1).
Sensing capabilities are significant in all fields, but smart build-ings and smart transportation, referred to as “built infrastruc-ture,” will represent markets of primary importance. In both fields, there’s a need for many different devices that can span from nodes providing basic monitoring to active nodes with a high computational capability. The rationales for the adoption of IoT in these fields are several, from social to environmental to economical. Energy conservation, environmental control, traffic optimization, infrastructure monitoring, accident pre-vention, and disaster containment are just some of the fields that can benefit from interconnected sensing devices.
Connected Cars
26 Embedded Computing Design | February 2015
■ Other■ Telemedicine■ Servers
■ Vehicles■ Smart meters/smart cities■ Security
60
50
40
US$
bill
ions
30
20
10
2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 20250
IDTechEx is forecasting the value of IP-addressed sensor nodes to increase from $0.68 billion in 2015 to $48 billion in 2025, constituting a 47 percent compound annual growth rate (CAGR).Figure 1
Besides a thorough knowledge of sensing capability, understanding the different communication characteristics of IoT nodes is of primary importance. Tradeoffs must be made when developing a solution, and a proper architectural study will enable the minimization of costs, maximizing system performances at the same time.
Characteristic of IoT nodesThe major characteristics of IoT nodes (Figure 2) include a sensor front-end, low-power signal conditioning electronics (typically an ASIC including a microcon-troller with embedded algorithms), power supply/storage/management, and back-end, low-power communications, usually wireless and enclosed in a package (see microelectromechanical systems-based (MEMS-Based) Systems Solutions for more information). The technological challenge for the implementation of such devices is limited to the integration and packaging of different existing components, as well as the availability of energy harvesters to make the node self sufficient.
In the IoT domain, networks can be classified as unconstrained (NTU) – characterized by high-speed communication links, offering transfer rates in the Megabit per second (Mbps) range – and constrained (NTC) – characterized by relatively low transfer rates, typically smaller than 1 Mbps.
The network taxonomy is also dependent on the type of terminal used. Unconstrained terminals have high computational power and a theoretically unlimited energy reserve, allowing them to implement complex tasks such as strong cryptography, HTTP traffic, and high transmission rates typical of NTU networks.
Constrained terminals show important limitations with respect to unconstrained terminals: a reduced transmission capa-bility, smaller than 1 Mbps; a limited energy reserve; a lim-ited data storage capability (typical values are 10 KB for RAM and 100 KB for ROM); and a limited computational power (less than 100 MHz). Finally, tag-type terminals show extreme limitations in computing power, memory storage, and energy storage.
Smart buildingsSmart buildings provide a quality and comfortable environ-ment, and increased safety and security while operating in an energy-efficient fashion. A typical example is the Nest “learning” thermostat. It consists of seven non-MEMS sen-sors measuring not only temperature and humidity but also presence, allowing temperature control based on occupant usage history.
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www.embedded-computing.com 27
MEMS FRONTEND
PACKAGING/INTERCONNECTS
Monolithic/Heterogeneous
Design for Manufacturing Test
Co-Design
Systems Engineering
• Sensor(s)• Actuator(s)• Structure(s)
SIGNALCONDITIONINGELECTRONICS
• ASICS• DSP• Microcontroller
POWER/CONTROLELECTRONICS
• Energy Harvesting• Battery
BACKENDCOMMUNICATIONS
ELECTRONICS• Wireless• Non-wireless• Networked
FUNCTIONS
DESIGNPRINCIPLES
MEMS-based Systems Solutions (MBSS) integrate critical elements of the Internet of Things (IoT) including sensing, computing, and communications to provide valuable measurements capability for smart building/smart transport monitoring and control applications.
Figure 2
The Bob and Betty Beyster Computer Science Building at the University of Michigan was recently instrumented by Professor Jerry Lynch of the Center for Wireless Integrated MicroSensing and Systems (WIMSS) with 15 Martlet wireless sensor nodes con-sisting of 45 channels of temperature, humidity, and CO2 sen-sors. The objective of the project, states Professor Lynch, is to “deploy a sensor network and model the environmental condi-tions as they relate to heating, ventilation, and air conditioning (HVAC) performance. The next steps include monitoring occu-pant’s behavior/presence and connecting the network directly to the control system of the HVAC system to achieve optimum performance versus cost.”
Smart transportMajor drivers for IoT adoption in transport are safety, conve-nience, fuel efficiency, and environmental pollution. Libelium has developed a system of sensor platforms measuring the presence of parked vehicles in Santander, Spain. This 400-node monitoring system includes magnetic sensors, signal conditioning electronics, a 7- to 10-year battery life, and a radio in a 12 cm diameter package. Data is transmitted to an access point on a nearby lamppost and relayed to the parking department headquarters where it gets analyzed and then sent to displays on the street. It can also be accessed by Internet-connected devices to direct vehicles to the appro-priate available parking spots. Additionally, another 600-node
system is mounted on lampposts and uses CO2 sensors to measure air quality.
Sensys Networks has developed a similar magnetic sensor-based system for use in traffic intersections. The system consists of a three-axis magnetometer, signal conditioning electronics with embedded software, and a radio in a 3" x 3" x 3" package that gets embedded at traffic roadways and intersections. This is clearly a lower cost solution to today’s large, 6' diam-eter magnetic loops. This package will be enhanced with a low noise floor, high-sensitivity accelerometer to determine vehicle classification based on axle counts and spacing using vibration signature analysis.
Sensys has also introduced “micro radar” sensor systems, installed at intersections and bike lanes. Consisting of a highly directive radar antenna operating at 6.3 GHz, the system can determine the presence of bicycles in a range from 1.2 to 3.0 m. The radar approach was adopted because a magnetic sensor can’t adequately detect the presence of people and composite materials of bicycles. Similar functionalities including signal pro-cessing, battery, and a radio are employed.
The U.S. highway system is a prime example of how a valu-able asset has been permitted to slowly deteriorate to the point where several bridges have collapsed, notably, the I-35W bridge over the Mississippi River in Minneapolis, resulting in 13 casualties. Many of the original highway roads and bridges constructed from the 1950s to the 1970s as part of the interstate highway system have exceeded their design life and traffic expectancy. Public funding has been limited to support adequate maintenance and repair. A recent study, Federal National Bridge Inventory, showed that 65,605 of 607,380 bridges were classified as “structurally deficient” (in need of rehabilitation or replacement because at least one of the major components of the span has advanced deterioration), and 20,808 were classified as “fracture critical” (without redundant protections and at risk of collapse if a single, vital component fails).
To directly address this severe situation, Michigan’s Professor Lynch has instrumented two bridges – the Monroe Michigan Telegraph Road Bridge and the New Carquinez California Bridge – with sensor nodes to determine the bridge’s struc-tural status under dynamic conditions. Built in 2003, the New Carquinez Bridge has 31 wireless sensor nodes deployed across the 1.056 km structure. A total of 87 channels of tri-axis accelerometers, strain gages, wind velocity, temperature, and potentiometer displacement sensors are measured using a proprietary Narada 4" by 4" printed circuit board platform that can accept up to four channels of sensor data.
Professor Lynch states that the purpose of the implementation was to determine the cost-effective deployment and robust-ness of the Narada sensor nodes and their remote sensors. Installed in 2011, the system is currently collecting data and is supported by the California Department of Transportation.
28 Embedded Computing Design | February 2015
Strategies Connected Cars
Data taken by the system will be used to validate the models developed by the WIMSS team and will be used to better understand the response of the bridge under conditions including high wind loading and earthquakes.
Professor Bill Spencer of the University of Illinois Urbana-Champagne and his team have instrumented the Jindo Island Bridge in Korea with 113 nodes (the largest deployment of its type for bridge monitoring) over the 344 m span. The 659 data channels are comprised of sensors including accelerometers to measure vibration in the bridges stay cables, strain gauges, anemometers for wind speed and direction, and temperature and light level sensors. The system was installed in 2010 and operated until 2012.
Professor Spencer stated, “In conjunction with our colleagues at Seoul National University, we have demonstrated that we can deploy a wireless autonomous measurement solution that’s robust and significantly lower in cost at about $100 per channel. This project has returned results as expected, and we’ve been able to better understand the wind loading algorithms and vali-date our models.”
New developmentsA solution for smart buildings currently being developed by Innoveering uses accelerometers and strain gages connected to a node/access point. The Enhanced Structural Collapse Awareness and Prediction Equipment (ESCAPE) application measures the structural integrity of a building during a fire and warns first responders of the building’s condition to keep them from harm’s way. This program is in the early stages of hardware and algorithm development.
Professors Babak Moaveni and Usman Khan of Tufts University are developing drone-based optical systems for the inspec-tion of bridges. Such inspection is currently conducted by engineers and maintenance personnel using visual methods. The Tufts researchers are exploring the instrumentation of drones with HD and IR camera to take pictures of the struc-tures, store the information on the drone’s memory system, and download the information when the drone returns to base. Using the drone pictures to detect cracks in the struc-ture coupled with vibration signature analysis is expected to achieve higher accuracy assessments of deteriorating struc-tures. A major advantage of this approach is that it uses a historically and highly acceptable approach of determining bridge structural deterioration – visual – which is expected to facilitate its acceptance by the maintenance community.
A cost/benefit analysis of IoT sensor nodesWireless autonomous sensor networks/IoT nodes have two main components: sensors and communication modules. It’s possible to classify communication devices according to their capabilities: unconstrained, constrained, and tags and system architectures must integrate various IoT nodes seamlessly. They’ve been in operation over the past years in different domains, but mainly in pilot projects. Based on research results, the major barrier to their widespread adoption is funding. Although many studies have established the aging nature of our roadways and bridges and their constant deterioration, this isn’t sufficient to motivate gov-ernment agencies to address these problems structurally. These conditions exist in Japan, China, and Vietnam, as well as the U.S.
We believe that a cost/benefit ratio should be used as a primary index for developing IoT nodes and monitoring systems. The replacement cost of the I-35W Mississippi Bridge was $234 mil-
lion, which is enough to instrument more than 20,000 bridges.
Roger Grace is the president of Roger Grace Associates, a strategic marketing consulting firm specializing in high technology.
Alessandro Bassi is currently an independent consultant, working on topics related to the Internet of Things (IoT), cloud storage, and smart cities, and has been a keynote speaker in more than 100 events.
Roger Grace Associates www.rgrace.com [email protected]
Alessandra Bassi Consulting www.bassiconsulting.eu [email protected] @bassiconsulting
30 Embedded Computing Design | February 2015
Strategies Connected Cars
E-magAutomotive E-mag Issue 2 opsy.st/AutoEmag2
E-castThree ways to ensure your automotive developers deliver secure, compliant, defect-free softwarePresented by Rogue Wave Software ecast.opensystemsmedia.com/515
NewsGENIVI Alliance to provide Android Auto interfaceBy GENIVI opsy.st/GENIVIAndroidAuto
More on… Automotive
Internet of Things
Innovation and collaboration in the Internet of ThingsWith the rapid development of an emerging area of embedded computing like the Internet of Things (IoT) comes the dreaded fragmentation that can hold it back from further growth. Companies are always thinking about how to make the IoT bigger and better, as you will see in the following executive speakouts and product spotlights, but interoperability is still a challenge.
“We don’t want to have smart people solving it one way over here and another way over there, and then have 15 different incompatible versions of the framework,” says David McCall, Senior Strategic Planner, Communication Frameworks, Intel corporation. “We’ve created an organization made up of some of the leading industry players and smaller companies who are interested in participating in this space, and we all come together and solve the problem once.”
The 50-member-and-growing OIC takes a unique approach by working on both open source code solutions and established
connectivity standards to combat fragmentation with scalability and interoperability across verticals.
“Everyone is developing really, really cool apps within verti-cals,” says Guy Martin, Senior Strategist, Open Source Group at Samsung. “We think that the next great thing in IoT and the future of IoT are those apps that go cross-vertical?”
As part of their work, the Linux Foundation is hosting developer collaboration through the IoTivity Open Source Project (www.iotivity.org), an open source software framework for IoT connec-tivity. The IoTivity preview release launched in mid-January and serves as a reference implementation of future OIC standards.
For more on the IoTivity preview release, see opsy.st/IoTivityRelease, and for the full interview with David McCall and Guy Martin from the Consumer Electronics Show, see opsy.st/OICQandA.
Industrial IoT Devices Demand Enduring, Decision-Quality DataBy Datalight www.datalight.com
As data storage demands for Industrial IoT (IIoT) edge devices such as intelligent sensors increase, new requirements for storage software are emerging. Datalight is bringing its exper-tise to these highly resource-constrained, hard real-time sys-tems through purpose-built products leveraging our data storage technology and expertise.
Many market-leading OEMs in the ruggedized segment of the industry have adopted Datalight’s flash memory and file system technology to create end-user products that are winning reli-ability awards and delighting their customers. Many of these products have complex use cases and multiple applications with products like handheld terminals, fleet management computers, industrial automation controllers, and medical diagnostic and treatment devices, so data storage has been a priority.
As designers make IIoT devices smarter, a common design goal is for the intelligent device to operate autonomously and adjust its behavior based on data-driven decisions. The goal is to save time, money, and even lives. The ability of the IIoT device to accomplish this mission hinges upon reliable avail-ability of decision-quality data. These emerging require reli-able storage over the entire lifetime of the device that won’t require a complex and risky software update or a trip to Mars to work around a failing flash memory device.
In the brave new world of IIoT, data can be rapidly collected and has potential to be transmitted up to the cloud for storage. But this doesn’t mean designers should neglect the integrity of their primary, on-device data storage. You might be thinking, “I don’t have to store it locally,” but is there a connection avail-able all the time? Will network data traffic cause an unrecover-able timeout? Have you accounted for degradation of hardware performance over time?
If the data on your device can’t be reliably saved or retrieved, it doesn’t matter how good you make your application or the hardware you produce. Reliable data storage needs to be treated as an asset and or it becomes a liability.
Internet of Things Executive Speakout
www.embedded-computing.com 31
Internet of Things Executive Speakout
Hyperconnecting the Internet of ThingsBy Jens Wiegand, CTO at Kontron www.kontron.com
Harnessing the Internet of Things (IoT) and making it a reality promises immense opportunities to companies worldwide, but it is not without some serious chal-lenges. Today, the market is fragmented and characterized by incompatible sys-tems and stovepiped solutions. To deliver a viable end-to-end IoT implementation requires an approach that removes the barriers between traditional information technology (IT) and operational tech-nology (OT) to form a hyperconnected infrastructure. IoT applications such as those supporting predictive mainte-nance, analytics and big data requires a holistic methodology so there is ample cohesiveness between hardware and software suppliers, service providers and communication infrastructure vendors.
Few suppliers are offering a broad breadth of IoT solutions today. Only solving a part of the problem has led to a lack of necessary interoperability. Individual islands of automation don’t provide the capabilities needed unless suppliers can integrate with the enter-prise aligning the entire solution. Taking this type of global approach allows com-panies to share data and analysis with partners or consumers, or take in data from other IoT sources.
Most organizations do not have the expertise to develop an end-to-end IoT solution. Suppliers end up supporting just a subset of capabilities rather than providing crucial technologies that meet multiple protocol requirements, the diverse set of application development strategies, trusted device insertion and management needs and real-time capa-bilities combined with enterprise scale and cloud-based services.
One-size-fits-all won’t workA good example of the challenges facing designers is in the development of industrial IoT (IIoT) that need to con-nect beyond one cluster of devices. Compounding the issue is these devel-opers rarely have a “greenfield” to work with. For developers to deploy applica-tions that enable an enduring IoT trans-formation mandates that they do more than plug devices into a common net-work protocol or use a single hardware and software development model for a set of pre-defined services. The com-plexity involved in a typical IIoT deploy-ment consists of:
õ Multiple connectivity protocols, both wired and wireless, call for gateway and protocol conversion capability.
õ Hardware requirements range from tiny, power-efficient microcontrollers to single-board computers (SBCs) and systems to massive, workload-optimized datacenter infrastructure.
õ Software frameworks vary in development approaches, programming languages, standards compliance, completeness, robustness and openness.
õ Services need to blend traditional information technology (IT) with operational technology (OT), integrating end-to-end capability from real-time performance to analytics.
To simplify these types of “brownfield” deployments, new development models are necessary. Hyperconnecting is a multi-faceted vision for how the IoT should be built. It allows events distant or near to be sensed, combined, interpreted, and understood – with the ability to access
actionable information whenever and wherever it is needed. Hyperconnecting allows end-to-end IoT implementations to combine the following attributes:
õ Sensor aggregation with multiple wireless protocols, including Wi-Fi, Bluetooth Low Energy (BLE) and ZigBee
õ Scalability across hardware platforms with support for ARM and Intel architectures
õ Co-existence of C and Java development with open application programming interfaces (APIs) and dynamic components
õ Flexible messaging including RESTful web services and DDS or MQTT for publish/subscribe
õ IT-style management such as trusted boot, role-based access, certificates, and authentication
õ Integration with leading enterprise databases and predictive analytics packages
End-to-end IoT ReadinessKontron is perfecting the approach to IoT. Its hyperconnecting architectures on a foundation of standards-based solutions fully enable development flexibility and enterprise integration with openness for future requirements. Backed by two decades of embedded computing evolution, Kontron can leverage extensive experience incorpo-rating thousands of real-world applica-tion deployments in the commercial, industrial, medical, and transportation markets, just to name a few. Kontron knows that to achieve IoT success means helping organizations develop true end-to-end solutions that also reduce costs and enhance revenue streams.
32 Embedded Computing Design | February 2015
IoT Security Done RightVitesse Semiconductor www.vitesse.com
Cisco’s most recent Visual Networking Index forecasts the number of devices connected to IP networks at nearly 2x the world’s population in 2018. This translates to almost three networked devices per capita by 2018, almost a 50% increase over 2013. And clearly our world’s connectedness to the Internet of Things (IoT) will only continue, as devices become even more widespread and sophisticated. Morgan Stanley fore-casts 75 billion devices will connect to the IoT by 2020.
With practically daily reports of security breaches, cyberse-curity will undoubtedly remain a hot topic. What many may not realize, however, is that resolving these security issues will be crucial to the IoT’s success. Think about it. Increasing the number of connected “things” multiples network endpoints exponentially, and each now represents a network vulnerability, especially given that hackers can theoretically compromise any-thing with an IP address.
Obviously, no single security initiative can stem all potential intrusions. But embedded systems designers will need to pay close attention to securing not only applications, but networks and devices themselves. Applications security now commonly uses Authentication, Authorization and Accounting (AAA), in conjunction with data confidentiality (encryption). However, this effort is futile if networks and devices are not subject to the same AAA principles. Particularly as the number of mobile devices connecting into embedded systems like traffic control networks or smart grid systems increases, the consequences of a security breach can become deadly. Imagine a rogue device swapped into a nuclear power plant network that fails to authenticate, authorize and account for each of its diverse end-points. The good news is that securing these last mile links is possible today with encryption technologies like IEEE 802.1AE with strong 256-bit encryption and link layer AAA. As an industry, we just need to be diligent enough to apply these technologies pervasively.
Internet of Things Executive Speakout
Martin Nuss, CTO Vitesse Semiconductor
www.embedded-computing.com 33
Deliver safe, secure mission critical software, faster with Rogue Wave Software• Prevent hacks and data breaches to safeguard your software
applications against threats, attacks, and security vulnerabilities.• Meet safety-critical standards and compliance, whether they are
government and industry standards or a company policy.• Build code confidence and have time to focus on creating
innovative apps.• Klocwork puts static code analysis at the desktop, identifying
critical safety, reliability, and coding standards issues in front of developers’ eyes – well before check in.
• OpenLogic offers an enterprise-class set of management, scanning, and support tools designed to simplify development and minimize risk of open source software.
• TotalView debugger provides unprecedented control over processes and thread execution, along with deep visibility into program states and data.
www.Roguewave.com
Revenue-Grade Data for Industrial Internet of Things Devices• Power failsafe reliability ensures complete data integrity• Improve flash memory endurance to extend the working life
of data storage• Fast performance to capture data quickly and completely• Pre-ported to Linux/Android, Windows Embedded Compact;
i.MX and OMAP processor families• Ask us about support for other operating systems, including
VxWorks!• Transactional file system field-proven by the leading
producer of IoT edge intelligence platforms
www.datalight.com/solutions/industries/industrial-internet-of-things
Internet of Things Product Spotlights
34 Embedded Computing Design | February 2015
IoT ready KBOX A-201• Embedded Fanless BOX PC• Internet of Things (IoT) ready• From Intel® Quark™ X1020 to Intel®
Atom™ E38xx• Maintenance-free• Soldered memory conception• Increases the flexibility,
serviceability and cost efficiency for various applications
www.kontron.com/products/systems-and-platforms/embedded-box-pcs/fanless-box-pc/kbox-a-201.html
Bluetooth modules• Bluetooth 4.0, Classic and
Smart Ready modules• Wi-Fi modules• Reliable and robust wireless
solutions for any application• 15-year industry veteran• >98% customer satisfaction• First to market with Bluetooth
Low Energy (BLE) modules
Hall 5 Booth #346 [email protected]
Europe +358 9 435 5060Americas +1 770 291 2181
Asia +86 21 6104 2277
RTPatch®: Binary Diff Patch Software Solution • COTS binary patch diff for all firmware, data and software
updating, including FOTA• Proven safe and reliable with billions of updates applied since
1991• Typical reduction 90+%• Supports any OS and hardware combination, or without OS• Small footprint, customization available, C source
code included• From industry leader Pocket Soft, established in 1986
pocketsoft.com
Internet of Things Product Spotlights
The IoT E-magThe Internet of Things E-mag deconstructs
the IoT with features that investigate device/network infrastructure,
comprehensive cyber security, reengineering business models, and much, much more.
http://opsy.st/IoTEmag
For more on latest news, articles, blogs, white papers, and products on the Internet of Things visit embedded-computing.com/topics/iot
www.embedded-computing.com 35
Web Accelerator platform The Suvola Web Accelerator is a secure and trusted web services appliance platform. The platform includes a low-latency HTTP server with reverse proxy, caching at the edge for content acceleration, security, and bandwidth management capabilities to provide a variety of front-end services for managing multiple application servers. The platform was designed to secure and accelerate cloud infrastructure workloads based on Freescale’s QorIQ multicore SoC products.
ARM CPU+FPGA module with dual OS monitor, TrustZone supportDAVE Embedded Systems BORA is a Dual Cortex-A9 CPI code with integrated Xilinx Zynq application processor. The SafetyGate (SafeG) dual OS monitor has also been ported to the BORA platform and takes advantage of the ARM TrustZone security extensions. BORA is suitable for ruggedized applications requiring small form factor such as medical instrumentation, advanced communications systems, real-time and safety applications.
DAVE Embedded Systems | www.dave.eu/home.html embedded-computing.com/p372565
Suvola | www.suvola.com embedded-computing.com/p372560
Multicore programming solution, high performance, fast time to market The SequenceL development environment is tailored for multicore and many-core programming applications. SequenceL provides a powerful functional programming language and auto-parallelizing tools for tuning code for multicore platforms. The platform plugs into Eclipse and Visual Studio IDEs, features an auto-parallelizing compiler, and a runtime environment that identifies available cores and allocates workloads to maximize utilization.
Texas Multicore | www.texasmulticoretechnologies.com embedded-computing.com/p372566
Editor’s Choiceembedded-computing.com/editors-choice
36 Embedded Computing Design | February 2015
March 9-11, 2015Santa Clara , CA
Learn how to design, build and develop apps for the wearable technology revolution at Wearables TechCon 2015!
• 2 Days of Exhibits
• Business-Critical Panels
• Special Events
• Industry Keynotes
www.wearablestechcon.com
Registration Today!
A BZ Media Event
“Wearables DevCon blew away all myexpectations, great first year. Wordscan't even describe how insightfuland motivating the talks were.”
—Mike Diogovanni, Emerging Technology Lead, Isobar
Two Huge Technical TracksHardware and Design TrackChoose from 30+ classes on product design, electronic engineering forwearable devices and embedded development. The hardware track is a360-degree immersion on building and designing the next generation of wearable devices.
Software and App Development TrackSelect from 30+ classes on designing software and applications for the hottest wearable platforms. Take deep dives into the leading SDKs,and learn tricks and techniques that will set your wearable software application apart!
ECD_Layout 1 1/5/15 1:13 PM Page 1
Floored: 2015 International CESBy Brandon Lewis, Assistant Managing editor
The theme of CES is connectivity – IoT, wearables, 5G mobile, and car connectivity, just to name a few specifics. See Brandon’s highlights of CES 2015 in this slide show.
opsy.st/CES2015Highlights
Some bold “embedded” predictions for 2015By Rich Nass, Embedded Computing Brand Director
What can we expect from 2015? That’s a great question, and it’s one I posed to our esteemed Advisory Board. In no particular order, here are their responses.
opsy.st/EmbeddedPredictions2015
Automotive E-mag
The second installment of the Automotive E-mag shifts into gear with features covering in-vehicle MCU consolidation, the importance of independent software for auto manufacturers, ISO 26262 and MISRA coding tools and techniques, connected car tech, and more.
opsy.st/AutoEmag2
Interoperability and the Internet of Things – To standardize or not to standardize?
Presented by ADLINK, RTI, ThingWorx
The Internet of Things (IoT) encompasses a range of technology verticals, from consumer electronics and connected cars to industrial controls and the smart grid. However, while this immense diversity has created a market opportunity valued as high as $14 trillion, it has also generated significant interoperability issues stemming from a vast amount of available communications protocols.
ecast.opensystemsmedia.com/520
5 minutes with ... Jim Ready, Chief Technology Advisor, CadenceBy Rich Nass, Embedded Computing Brand Director
In this weekly video series, Rich Nass talks embedded with industry heavyweights on various topics. In this installment, Rich and Jim Ready discuss the state of education and addressing business challenges.
opsy.st/5MinutesWithJimReady
Top 3 strategies to reduce risk in automotive/in-vehicle software developmentBy Rogue Wave Software
Development teams, especially the managers who are ultimately responsible, face incredible challenges when building in-vehicle applications, and are learning that team members need to do more than just catch code defects during verification and validation testing. The new imperative: Identify and address security and compliance concerns earlier in the lifecycle, all while delivering innovative and differentiating features.
opsy.st/AutomotiveRiskStrategiesWP
E-cast
VIDEO
WHITE PAPER
Blog
Blog
E-mag
WEB •••õ WIRE Videos • Blogs • News • E-casts • White Papers
38 Embedded Computing Design | February 2015
Watch
AN EVENT OF
The mobile communications revolution is driving the world's major technology breakthroughs. From wearable devices to connected cars and homes, mobile technology is at the heart of worldwide innovation. As an industry, we are connecting billions of men and women to the transformative power of the Internet and mobilising every device that we use in our daily lives. The 2015 GSMA Mobile World Congress will convene industry leaders, visionaries and innovators to explore the trends that will shape mobile in the years ahead. We’ll see you in Barcelona at The Edge of Innovation.
WWW.MOBILEWORLDCONGRESS.COM
Thinking beyondthe board
Sometimes our off the shelf products are not the perfect fi t. Our appli-cation engineers and in house design talent are ready to develop customized solutions for your system requirements. Our stock products are accessible to use as building blocks for your next project. Calling WinSystems connects you directly with an Application Engineer who is ready to discuss customization options for fi rmware, operating systems, confi gurations and complete designs.
Team your engineers with ours to move your product from concept to reality faster.
715 Stadium Drive I Arlington, Texas 76011Phone: 817-274-7553 I Fax: 817-548-1358 [email protected]
Call 817-274-7553 or visit www.winsystems.com.Ask about our product evaluation!
Single Board Computers COM Express Solutions
Power SuppliesI/O Modules
Panel PCs
Small Form Factor ComputersIntel® Atom™ E3800 and i.MX6 CPUs
Fanless -40° to +85°C Operation
Small Form Factor Computers
EPIC Single Board ComputersRugged, Stackable Form Factor
Fanless -40° to +85°C Operation
EPIC Single Board Computers
PC/104 Single Board ComputersRugged, Stackable Form Factor
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PC/104 Single Board Computers
