Jim Lipman, Sidense Corp.
The Internet of Things (IoT), sometimes called the Internet of Everything (IoE), refers to an evolving and rapidly expanding global ecosystem comprising the connection via the Internet of all kinds of common objects with embedded electronics, and the processing of the data collected, shared and stored in “The Cloud.” Small embedded controllers, actuators and sensors as well as larger, more complex communications and computing systems will be tasked with acquiring, storing and processing mountains of information. Consequently, this will also significantly increase Internet traffic, along with the need for computing resources to exchange, store and process all the data.
IoT can be considered as a highly intelligent type of Machine-to-Machine (M2M) communication coupled with sensor-based data gathering and processor-based decision making. Within the IoT ecosystem, MCUs and other processing engines will be tasked with learning and sorting vast amounts of acquired information to provide meaningful results to either other machines or to humans. While long-range forecasts vary widely, it is generally believed that IoT will drive unprecedented volumes and demands for the electronics industry. IoT is poised to open the door for IP vendors, silicon foundries and software designers to develop products for literally tens of billions of connected devices over the next few years. In a recent article the Internet Business Solutions Group (IBSG) at Cisco predicts that there will be 25 billion devices connected to the Internet by 2015 and 50 billion by 2020.
The explosion of information that IoT devices will gather will require huge numbers of processors to process and manage the data from these IoT devices along with lots of low-cost, secure and reliable embedded non-volatile memory (NVM) for code storage, sensor trimming, device configuration, security keys and other storage functions. Virtually every one of the projected billions of IoT devices can use some amount of one-time programmable (OTP) memory.
The IoT ecosystem, comprising a vast number of data gathering and data crunching devices, will impact a very broad range of market segments, including but not limited to the following:
- Industrial (utility Smart Meters, equipment wear-out sensing, manufacturing control, climate control)
- Consumer (smart home control including lighting, security and comfort, product ordering, energy use optimization, home maintenance)
- Retail (tracking, inventory, focused marketing)
- Medical (implanted and wearable devices, remote patient monitoring [telehealth])
- Automotive (parking and traffic flow, smart key entry, location, anti-theft)
- Environmental (endangered species tracking, weather prediction, resource management)
- Military (resource allocation, threat analysis, troop monitoring)
- Agriculture (crop management, soil analysis)
In an IoT world, there will be many new interconnected devices that incorporate sensors, data processors and the wireless communications capability needed to transfer information to and from other devices. For example, in preventive and curative telehealth applications an implanted or wearable sensor-equipped IoT device can monitor a patient and, if a problem is detected, alert a physician, who can then decide what corrective action to take, including remotely administering medication to the patient. Going a step further, pre-determined guidelines might even result in remote medicating without any human interaction. Along with the multitude of completely new devices, some existing device designs will have variants updated with wireless capability to allow them to operate in an “IoT universe.”
IoT Impact on Hardware
Gathering and analyzing the massive amounts of data that IoT devices will collect will require very large numbers of sensors and processors. Some simple controller and other processing functions will be done by remote devices, but a large part of the data processing will take place by servers and other computing devices in “The Cloud.” In addition, having wireless communication capabilities on IoT devices also means that they will need to include appropriate communication cores. This will generate many requirements for embedded NVM in all of these devices.
Code storage is critical for the processing engines that will be analyzing and processing the environmental and other IoT-generated data and then deciding what to do with the results of their analyses. In addition, simple data-gathering devices will use OTP for configuration and for executing simple instructions. There will be situations where the stored code and configuration data will need to be updated in the field, possibly remotely. This can often be done with OTP used in an emulated multi-time programmable (eMTP) mode by reserving additional, un-programmed OTP space for new data and allocating some additional storage for a tag to keep track of which memory segment is currently being used. Updatable encryption keys also can be implemented using OTP in an eMTP mode.
Non-volatile memory for IoT devices will need to meet the following general requirements:
Minimize Cost and Area
Because many IoT devices will have to be very inexpensive and small, it is important to minimize the silicon area of these devices. In addition, silicon IP embedded in these chips, such as memory, should not only be as small as possible, but should minimize any additional wafer processing cost due to extra masks or processing steps.
To perform such tasks as setting user preferences or updating keys, embedded non-volatile memory will need to be programmable not only during chip manufacturing and test but also in the field with the chip installed in end-user equipment.
Minimize start-up time
Embedding program code in on-chip NVM and executing this code in-place improves overall device performance by avoiding the need to copy code to on-chip RAM on power up from external memory such as a separate EEPROM chip. Ideally the NVM should be fast enough to allow executing code directly, avoiding the need to copy code to RAM for execution and reducing boot-up time and the on-chip storage requirement for RAM, which further reduces chip cost.
Low Voltage, Low Power
Many devices that will be connected in the IoT ecosystem will run on small batteries. In remote sensor locations, where battery replacement may be difficult or even impossible, power for wireless sensors may come from energy harvesting, either used directly or for recharging a small battery. These devices would convert the energy from motion, light, heat or an electromagnetic field into the electrical energy needed to power the sensor and, in some cases, an integrated processor. In these situations, the sensor, processor and any embedded memory would have to have low standby and operating power dissipation.
Provide Secure Data Storage
Many applications involving the exchange of sensitive data, such as point-of-sale and financial transactions, will require high code, key and data security. The memory that stores this information thus must have a high level of physical security and be extremely difficult to reverse engineer.
1T Antifuse OTP for IoT Applications
To meet these needs, antifuse one-time programmable (OTP) memory is an ideal fit .One type of memory is particularly well suited – NVM based on Sidense’s Split-Channel 1T-OTP architecture (1T-Fuse™). 1T-OTP minimizes bit-cell area (and the impact on total chip area) while allowing the OTP memory to be fabricated in standard CMOS processes with no additional masks or process steps.
Programming the bit-cell from a “0” to a “1” is done using an integrated charge pump that runs off normal chip voltages. The programming is controllable and irreversible. All programming occurs in the transistor's channel region for high reliability and repeatability.
Inherently, antifuse-based 1T-OTP is more secure than floating-gate MTP architectures, such as flash memory, and other types of OTP, such as ROM, eFuse or EEPROM. Antifuse 1T-OTP has no stored charge and programming does not visually change a bit cell. This makes detecting antifuse OTP bit-cell states almost impossible using current/voltage scanning, reverse engineering or de-layering techniques. 1T-OTP macros also have additional features to enhance security of stored information, making them ideal for safe storage of encryption keys for secure wireless communication.
The small size of the one-transistor bit cell in 1T-OTP macros results in a small memory footprint. Coupled with 1T-OTP fabrication in standard logic CMOS processes, this minimizes chip size and silicon cost.
1T-OTP operates over wide temperature ranges, up to 150°C in some implementations. This is particularly important for reliable operation of devices deployed in remote locations and in higher temperature industrial and automotive environments.
Providing fast read access time, 1T-OTP supports direct code execution from the OTP in many cases. This saves boot time and reduces on-chip RAM requirements, further reducing device cost and increasing performance.
1T-OTP macros are programmable at test and in-field. Since IoT devices will typically not need frequent stored code or encryption key updating, the small 1T-OTP footprint allows designers to include extra memory capacity for field-updates in a small area, allowing the memory to be used in an emulated Multi-Time Programmable (eMTP) mode. This includes code patching, where small sections of code can be updated rather than updating the entire code footprint.
1T-OTP macros feature low active and standby power, which is necessary for IoT devices that have demanding low power and low energy constraints.
Example using 1T-OTP for an Embedded IoT Device
The following is an illustration of how 1T-OTP can fulfill many NVM needs in an embedded wireless SoC for IoT-connected equipment.
The Application Microcontroller core uses 1T-OTP to store boot code. The Wireless LAN Controller and RF circuitry also use the same 1T-OTP to store boot code to enable the chip on power-up and also for highly secure storage for encryption keys and secure communications. The chip also uses 1T-OTP to provide trimming for external environmental sensors, to store configuration settings to adjust and configure analog circuitry during test and assembly, and for in-system/in-field adjustments in final equipment. Other potential uses of 1T-OTP in IoT applications include data logging, power management for a battery or operation from energy harvesting, device identification and setting user preferences in the field.
Lots of Devices – Lots of NVM Opportunities
Despite different projections of actual numbers, there is general agreement that the Internet of Things will involve very large numbers of interconnected data gathering and data processing devices. The billions of sensors, controllers, communication and computing systems in an evolving IoT ecosystem, comprising both simple and highly complex devices, all present opportunities for various types of embedded memories.
Sidense 1T-OTP has several attributes that IoT devices require in their embedded memories, including low cost, low power consumption, field programmability, high security and high reliability. 1T-OTP macros cover a wide range of configurations and are available over a broad range of process nodes and variants, from 180nm down to 20nm, including high voltage and BCD implementations, and are under development for smaller processes. As a key component in many IoT devices for storing code, keys, trimming parameters and configuration data, 1T-OTP is prepared for the IoT explosion.
Jim Lipman is Sidense's marketing director. His work experience includes positions at TechOnLine, VLSI Technology, Hewlett-Packard and Texas Instruments. Jim has a D.Eng from SMU and an MBA from Golden Gate University. He can be reached at email@example.com.