DASH7 IoT Wireless Stack
DASH7 is both a new technology and an old one. Its roots from ISO 18000-7 began in the early 2000’s, having been deployed in large quantities for military supply chain networks. DASH7 as we know it today is a result of a top-to-bottom modernization of the technology that began in 2008, and which continues.
Design goals have been oriented to meet applications not readily solved by other technologies. For example, a primary objective of DASH7 is to create an ad-hoc network of 1000 devices and securely pull data from all of them within 10 seconds or less. This may seem superfluous, but it is absolutely important for networking with sensor that may be passing-by in a vehicle. It’s the only technology capable of this feat apart from NFC, but DASH7 communicates over hundreds or thousands of meters, and NFC is a < 1m technology. Other features of DASH7, like high-security, long-range, filesystem architecture, and ultra-low-power operation have stemmed from this basic yet demanding objective.
Presently, integration and consolidation of IoT wireless technologies is not apparent. Quite the contrary, it has become increasingly fragmented. Recent endeavors like LoRa and SigFox have gained a lot of attention, and they eschew standards organizations such as ISO, IEEE, and IETF altogether. DASH7 represents a wireless stack that blends the best (and compliant) features of a traditional IEEE/IETF stack with the best features of others. It is flexible enough to be a viable integration partner with 802.15.4g, LoRa, NB-IoT, LTE, and NFC technology roadmaps. Haystack is working towards DASH7 integration with these systems, and ultimately consolidation onto multi-protocol silicon.
LPWANs are a relatively new entrant into wireless IoT, with major offerings coming in the form of SigFox’s proprietary network, which is supported by multiple technology vendors, and Semtech’s open LoRaWAN network, which is limited only to Semtech technology components.
LoRaWAN is more operationally flexible than SigFox is, but ultimately they are similar: they are both cellular-like networks that support ultra-low-data rate uplinks. Downlinks, from the network to the endpoint, are not strongly supported. In other terms, they are high-latency one-way networking solutions.
Haystack’s real-time, 2-way networking can be emphasized as solutions for the following applications that aren’t generally met by contemporary LPWAN networking.
What’s even better, is that DASH7 is easy to integrate with LPWAN technologies like LoRaWAN, NB-IoT, and even SigFox (if SigFox allowed it). In all of these cases, integrating DASH7 is merely a firmware upgrade, as it is compatible with each of these radios. The table below tells the story of the DASH7 stack integrated with LPWANs, as described above, as well as an integration with NFC (NFC integration is described in greater detail, in the next section). In the special case of NB-IoT, DASH7 can provide a full featured IoT stack where there is currently no stack at all, and it’s 100% compatible with the NB-IoT stack requirements.
DASH7’s origins are from the ISO 18000 standard, which defines a series of RFID and WSN technologies. For example, ISO 18000-2 defines a set of low frequency (~125 kHz) deployed widely in automotive and agricultural applications. ISO 18000-3, -5, and -6 define passive RFID technologies at various frequencies. ISO 18000-7, as you may have guessed, is the origin of DASH7.
The origin of NFC is a combination of ISO 18000-3, ISO 14443, and ISO 18192, and NFC has been a natural partner of DASH7 from the beginning. Even though they have extraordinarily differently features — one is a proximity communication system and the other a long range wireless networking technology — they share data interchange formats that allow full stack compatibility. What’s more, DASH7 is designed to perform exceptionally well on narrowband, mid-frequency radios (such as 433 MHz). Such radios have nearly identical architecture to NFC radios, and they may share the NFC antenna as well. At present, DASH7 is the only wireless IoT standard that can integrate easily with NFC.
One of DASH7’s unique attributes is its sophisticated, data-driven MAC layer that can arbitrate different configurations of frequency, channel, code, and time multiplexing. This makes it the only IoT stack at present time that can support the requirements of contemporary point-to-point LTE modes. Additionally, it is perfectly suited to allow future migration to the LTE Cat-M1 PHY and data-link, also known as “NB-IoT.” The NB-IoT specification is presently in draft, but the low-level requirements for the radio layer (PHY) are available, and it too requires a degree of channel and time multiplexing agility not feasible with most existing IoT technology roadmaps. As we wait for standards to consolidate in this industry, DASH7 provides frequency, channel, and standard-agility required for a future-proof roadmap, with universal application support, to NB-IoT plus contemporary radio technologies.
Health & Life Sciences
Mobile Advertising & Augmented Reality (AR)
HDO forms the foundation for the Haystack DASH7 Platform. OpenTag is the smallest, fastest stack for low power wireless networks available today. Haystack is a major backer of OpenTag. Most Haystack improvements to OpenTag eventually are re-submitted to the community under the OpenTag License (a superset of the BSD license).
Energy Harvesting for the IoT
After testing all options — RF harvesting, vibration harvesting, kinetic harvesting, and solar harvesting — we determined that solar harvesting is the best solution for a majority of use-cases. Solar panels are inexpensive and readily available, and they can produce a large amount of power. The solar panel we use in our HayTag, pictured to the right, is capable of producing as much as 20mW. This might not seem like a lot of power, but consider that HayTag only averages about 30µW as it runs, and when it is transmitting it is outputting less than 10mW of radio power.
In outdoor light, HayTag will charge fully in a matter of hours. In doing so, more power is flowing through the HayTag’s internal power circuits than ever flows out of its antenna. There is a huge potential for the charging process to create debilitating noise in the system, and only with extremely rigorous electronic design can one get the noise to an acceptably low level. Take a look at the sensitivity chart below, which is courtesy of Semtech. Semtech’s LoRa radio (one of the several radios Haystack supports) has high sensitivity — the negative numbers on the Y-axis reveal ever greater sensitivity as Y goes up. Here’s a big problem: -120dBm is a tiny amount of power, specifically 0.000 000 000 000 001 Watts. -140dBm is 100 times less than that. In order to successfully receive a signal at -140dBm, this chart shows the noise level must be -146dBm or lower. That level of noise is virtually impossible to achieve in any electronic system, much less one that is performing energy harvesting, yet Haystack’s low noise energy harvesting technology meets this requirement.
Long Range, Low-Power Wireless Communication
Wireless communications are conducted in a medium shared by all wireless devices as well as all electromagnetic energy. Noise is always present: sometimes more, sometimes less. Noise causes data errors, which causes packets to be lost. When packets are lost, energy is wasted and the communication range decreases. Good error correcting schemes can help both. Haystack uses error correction similar to that used by NASA’s Voyager ground stations — a limit-approaching scheme most suitable for short, bursty packets. It allows our technology to send data more efficiently than others, thus both improving the range and decreasing the power.
In the laboratory environment, it is easy to test wireless systems without interference from other wireless systems. However, the real world is full of wireless packets interfering with your packets. In a low-power network with high sensitivity, this can become a real problem no matter how advanced the basic error correction coding is, and no matter how advanced the spread spectrum modulation is. Testing a mid-data-rate LPWAN in the presence of a nearby smart electric meter tells a horrible story; the high power bursts coming from the smart meter wipe-out roughly two bytes of of the LPWAN data, enough to overwhelm the basic error correction of this system and cause a loss of the packet. Haystack’s solution to the problem is its Reed Solomon packet error correction technology. The Reed Solomon technology can repair large sections of the packet that are grossly corrupted or missing, such as the bytes that are victims of cross-talk by this high-power interferer in the plot to the right.
Haystack’s DASH7 systems are designed with the Voyager Code error correction algorithms built in. 35 years ago, such technology was relegated to mainframe computers, but today’s 32 bit ARM Cortex-M CPUs are sufficient to enable such algorithms. As it turns out, to increase efficiency Moore’s Law can be effectively applied to the data domain, but there’s not such a convenient method to reduce the power of a wireless transmission. So, to improve the efficiency of the network, the most important feature is to minimize the amount of time devices are receiving and especially transmitting data. DASH7 achieves this in four primary ways, all of which exploit the relative surplus of compute power on modern IoT devices. As a result, DASH7 devices tend to require roughly an order of magnitude less power than comparable wireless devices, even when they are running on similar silicon. Haystack’s IP portfolio is largely concentrated on these technologies.
Security & Cryptography for IoT
In the mid 2000’s, the EPC standards committee determined that filesystems were so critical for security, that they should be implemented on such ultra-constrained devices as EPC passive RFID tags. It took them quite a while to arrive at this decision (years), but by 2010 it was generally accepted.
The importance of the filesystem to information security is in the way files can be attributed with different privileges and access levels. In other words, they allow for multiple users, multiple users allow for multiple cryptographic keys for communicating data at different access levels, and that is what protects the important data on the device from hackers who may have cracked a lesser access level.
Haystack’s DASH7 filesystem is compact and offers features more common to a database than a PC filesystem, but importantly it has all the features needed to meet security requirements. Important data that controls the way the device works can be set as read-only and only accessible by network administrators, or even the manufacturer. Other data can be made more or less accessible.
Take a look at the image of the penguin, below. The top image in the montage is the original. Shockingly, the middle image is encrypted using AES cryptography, which is known to be very secure and is used in just about everything, but it’s very easy to detect patterns that emerge through the encryption. This image it is not ciphered properly, and as a result the underlying data is vulnerable. The bottom image in the montage represents properly ciphered data, which appears as noise.
It may seem trivial to apply a good cipher, but recent history is full of easily avoidable catastrophe. Not too long ago, Adobe’s password system was hacked because they were not ciphering properly — ZigBee has had similar incidents. One would think Adobe and Freescale should have enough security acumen to know better, but obviously they didn’t — yet another example of the dangerous lack of knowledge of security and cryptography in the IT community.
Haystack has pioneered implementation of the EAX cipher for IoT wireless, one of the two most advanced ciphers available for AES cryptography. Unlike any other widely known communications protocol in the world, in addition to simply protecting the payload data, Haystack’s EAX encrypted DASH7 protocol is able to encrypt most of the protocol information itself.
There are two primary ways to do public-key handshaking: the RSA model and the Diffie-Hellman Model. For battery-powered IoT endpoints, both methods are very suitable, as it is impractical to perform extensive attacks on such devices, and succeed, before depleting the battery. However, for battery-powered IoT endpoints, the problem is often doing a public key exchange at all, by any means. Consider the following:
As a result, public key cryptography has not thrived yet in IoT sensor networks, despite the fact that modern ARM Cortex-M CPUs are capable of meeting the computation requirements quite easily. Instead, much emphasis has been on using SIM card providers to supply “secure elements” for provisioning LPWAN devices. This adds cost and complexity that is unnecessary in a system compatible with Haystack’s DASH7. LPWAN builders may want to consider adding the DASH7 stack alongside their LPWAN stack, as DASH7’s public key exchange firmware could improve security and operational flexibility beyond what SIM elements can provide, at reduced cost.