Nordic Semi Rolls Integrated Module of IoT-Ameya360电子元器件采购网

Nordic Semi Rolls Integrated Module of IoT

发布时间：2018-01-31 00:00

作者：Ameya360

来源：Nitin Dahad

阅读量：2745

　　After three years in development by teams in Finland and Norway, Nordic Semiconductor introduced a system-in-package (SiP) module for low-power Internet of Things (IoT) applications.

　　Nordic's nRF91 integrates an LTE cellular model with narrow-band IoT (NB-IoT) connectivity in a 10x16x1.2mm package. It also incorporates a transceiver, RF front end, dedicated application processor, flash memory, power management and crystal and passive components.

　　After announcing last month that lead customers were already sampling the nRF91, Nordic revealed details of the device at an event in Oslo last week. During the event, Nordic also demonstrated the nRF91 operating on the Verizon Wireless Network in the U.S. and on the Telia network in Norway.

　　The nRF91 SiP is aimed at secure, low power, cellular connected IoT systems. Jointly developed by Nordic’s specially assembled cellular design team in Finland, and low power team in Norway, the chip was developed from scratch to optimize the power, cost and size savings enabled by the new LTE-M and NB-IoT cellular standards.

　　Nordic says the custom SoC combines the benefits of traditional cellular modules — including tele-regulatory and cellular certifications — with ease-of-use and the smallest form factor ever seen in the cellular industry to date. According to the company, the module has up to three times smaller footprint than other solutions on the market and a lower external bill of materials (BoM).

　　The module features 23 dBm output power and a -108dBm sensitivity receiver in the 700MHz-2.2GHz range. It also has a throughput of up to 360kbps with LTE-M and 60kbps for NB-IoT.

　　Nordic said it worked with Qorvo as a strategic partner for both the RF front end and the SiP development and manufacturing. The nRF91 Series supports global operation with a single SiP variant is a result of the combination of Nordic’s multimode LTE-M / NB-IoT modem, SAW-less transceiver and a custom RF front-end solution from Qorvo.

　　With security becoming increasingly a critical consideration in IoT systems, the company says it needed to have a processor with a built-in security platform.

　　"Security is the main reason we went for the Arm Cortex-M33 processor and Arm CryptoCell-310 security IP," said Peder Rand, product manager for cellular IoT at Nordic, in an interview with EE Times. "Its architecture brings the TrustZone technology to the embedded space."

　　This integration enabled an entire low power cellular IoT application to be implemented on an nRF91 SiP. The built-in host processor features TrustZone for Armv8-M, helping secure application data, firmware, and peripherals using an isolated, trusted execution environment across the CPU and system.

　　The SiP also features built-in support for positioning via an integrated assisted GPS (A-GPS) solution that combines cellular and GPS technology to deliver fast and accurate positioning.

　　Rand said key target areas initially for the device are in asset tracking, predictive maintenance and healthcare. He said people want to know where their "things" are and in what condition they are in. In healthcare, Nordic is aiming for the professional monitoring of patients’ vital signs in their own homes.

　　Rand said that in these applications, small physical size, low power, reliable connectivity and security are essential. The company expects general sampling in the middle of this year and volume production by the end of 2018 with lead customers.

　　Nordic says Telia and Verizon are key network partners. Rand said that while Nordic’s business model is to sell electronic components to OEMs and ODMs, these customers need a carrier that enable them to deliver IoT connected products.

　　Telia says it is experiencing an unprecedented demand for dedicated IoT connectivity represented by LTE-M and NB-IoT. These technologies enable products and services that wouldn’t otherwise be possible. In Nordic’s press release, it added that access to components has so far been scarce and has hindered large scale commercial launches.

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Trade news

IoT Merging Into Data-Driven Design

The Internet of Things is becoming more difficult to define and utilize for an effective business strategy. While an increasing number devices send data to the cloud or some local server, so much data is being generated and moved around that new strategies are being developed to rethink what needs to be processed where.Back in 2013, when the IoT concept really began taking off, connectivity to the Internet was considered the ultimate goal because the biggest compute resources were still in the data center. Today, compute resources are becoming more distributed and processing is becoming more nuanced. In fact, almost all of the early major proponents of the IoT, such as Cisco, Arm, Samsung and Philips, have shifted their IoT focus to data management, processing, and security.The big issues now are how to connect different devices to each other, and what to do with all the data generated by tens of billions of sensors and devices. That includes what data should be processed where, how much really needs to be moved, how to move it more quickly, and how to protect data in place and in transit.“When the IoT first started, a lot of it was based on things like temperature sensors,” said Geoff Tate, CEO of Flex Logix. “There’s not a lot of data coming out of temperature sensors. But now we’re adding in things like video, where you have cameras doing surveillance. Processing now has to be done closer to the camera—either in the camera or at some edge server. There’s also a cost for the radio chip to send everything, and not everywhere has good enough connectivity. On top of that, networks were designed for transmitting large amounts of data, not uploading it.”Fig. 1: Monthly visual networking data growth in exabytes. Source: Cisco visual networking index forecastThis adds a whole different slant to the IoT concept, because it means more data now needs to be processed in place or nearby.“Even with 5G, there is a huge amount of data being produced,” said Mike Fitton, senior director of strategic planning at Achronix. “What’s changing is that processing capability will move from the data center and flow toward the edge. Processing will need to happen everywhere. You’re going to see a shift in relative ratios along those lines.”Alongside a growing volume of data is an increasing value to the data. And the more data that is collected from more sources, the greater its value. But that value doesn’t necessarily rely on being shipped to the cloud where it can be mined in the context of other data. Some of it can be used by other devices or even by infrastructure.These shifts are behind last month’s merger of the Industrial Internet Consortium (IIC) and the OpenFog Consortium, which combined the networking standards and architecture development of the OpenFog Consortium with the IIC’s emphasis on testing product integration. The IIC is concerned with devices spread around the network, while the OpenFog Consortium is concerned with the networking, storage and processing infrastructure necessary to efficiently connect everything between the edge and the cloud. The merger of the two groups reflects the evolution of technology rather than a purposeful direction by either one, said IIC President Bill Hoffman.“Over three years of working on fog computing and trying to address bandwidth issues and the trend of AI moving toward the edge, it became clear we shared members and interests and problems that we’d been trying to solve,” Hoffman said. “We reached a point that we could streamline the way we drove technology deliverables and improve the overall market to consolidate discussion of fog computing and the IoT in one place.”IIoT and the edgeYet it remains to be seen how effective this approach becomes. The electronics industry is littered with devices that either never caught on, used far too much power, had too little performance, missed the market entirely, or which got lost in a sea of similar products.And while most IoT watchers point to the IIoT as the place where the real benefits are, successful IoT strategies are harder to develop than initially thought. A May 2017 report by Cisco showed that nearly 60% of IoT initiatives never made it beyond the proof of concept phase, and one-third of completed projects were failures.“You see some industries — mining definitely has a need, and manufacturing and a few others — but overall, across most industries we don’t see much engagement,” said Matt Vasey, OpenFog chairman and president, and also a director of AI and IoT business development at Microsoft. “A lot of industries just haven’t picked up in full force.”The reasons are varied, and sometimes specific to a company or industry segment. “It’s a great amount of transformation to really take advantage of edge and IoT, so there’s a lot of resistance from production,” Hoffman said. “There is also not a lot of metrics out to demonstrate the value. If you can save 50% on the cost of a process, that’s clear, but most of the benefits are less clear than that.”This doesn’t diminish the value of the data collected by sensors in smart devices, however. “If you can do something as simple as decrease fuel consumption by 1% by utilizing that data, that’s a huge impact,” said Achronix’s Fitton. “This is the kind of stuff that’s happening in the industrial IoT, and that’s having more impact than the classic definition of the IoT, which was always dismissed as something of a vague term.”The key is being able to tailor a solution that works, in a market where it makes sense. And even then, there is a confusing array of tools, platforms and strategies. In June of 2017, IoT Analytics counted more than 450 software packages being offered either as operating systems or system software connected networks of IIoT devices. Even if the tally was right, 450 options is chaos, not progress, according to a May, 2017 McKinsey report. “If there are [even] 100 IoT platforms, then there is no platform, just aspirants,” the report concluded.IEEE and a pair of industry groups formed to make sense of the growing edge computing trend may help reduce the chaos in this segment. Last June, the IEEE Standards Association, at the instigation of the IEEE Communications Society, adopted the OpenFog Reference Architecture as an official standard, now called IEEE 1394. That standard looks at east-west flow of data, rather than just north-south, which is a significant departure from how the IoT concept originally was laid out by leading proponents.“We have seen a continuum of intelligence extend from the cloud right down to the edge,” said Vasey. “We are trying to make sure we have the right tools for the job—near the edge where devices might need storage and servers, or just mid-tier gateways, to near-edge data centers with much richer resources—and extending right up to the cloud in a coherent way. We’re no longer dealing with just the cloud or just the edge or just the middle tier. It’s more of a continuum. And we get feedback from customers saying that model makes a lot of sense, putting compute and storage and networking resources anywhere up and down that continuum where you need it.”Thinking differentlySo what does this mean for the IoT as a whole? The key may be thinking about the overall concept less from the standpoint of the initial IoT vision and more from the flow of the data.“There’s a need for a lot more compute at the source of the data,” said Susheel Tadikonda, vice president in Synopsys’ verification group. “The volume of data is taking so much power and bandwidth, and latency is so much of an issue, that you need to consume the data at the source. If you can make the sensors intelligent, then they can evaluate the data without much delay and take immediate action. What we’re seeing is that everything is going together in bundles of data.”Tadikonda noted that while the data isn’t new, the emphasis on using it more effectively is definitely new. “No one cared about it in the past. The underlying data was very powerful, but no one had any idea of what it would spawn. If you look at Uber, no one knew something like that would happen until 4G technology and processing power was there. Traditional cloud solutions were implemented with central servers and storage. Now we are seeing an alternative to that with both storage and compute as close as possible to the edge devices like sensors. But data still has to be transmitted, and bandwidth has to increase because even if you do more processing locally, the number of connected devices is growing so fast that they’re producing more data in total.”This, in turn, is affecting how systems are being designed, from the data center to the networks and all the way down to the various components that make up chips.“We are moving into a data-driven economy,” said Lip-Bu Tan, chairman and CEO of Cadence. “It’s all about data. A lot sensors collect data. Depending upon the application, some will move into the intelligent edge. When you process the data there, you want to do that with very low power. That can drive productivity and efficiency. The other piece of this is the hyperscale data center. You need infrastructure there to drive the applications.”Security issuesAlongside of all of this, data has to be protected.“Now the question is how we evolve that so that we can build systems that are connected but secure, because there are more and more connected systems,” said Helena Handschuh, a fellow in Rambus’ Cryptography Research Division. “We need more end-point security. If you look at the PC industry and networking, there are ways to detect security issues and then try to mitigate them after that. But no matter how good your security, eventually something will go wrong.”Security was always one of the top concerns cited when it came to the IoT. Despite the warnings, the chip industry is just beginning to take a serious look at how to automate some of those checks. One of the drivers of that shift was the cost of fixing hardware—measured both in time spent on mitigating the problem and in performance inside of data centers—after Google Project Zero exposed hardware vulnerabilities related to speculative execution and branch prediction. Prior to that, a botnet attack based on the Mirai virus, brought down some of the largest Internet sites.“Security of a chip is something like compatibility,” said Wally Rhines, CEO Emeritus at Mentor, a Siemens Business. “You can always show that something is incompatible. You can never guarantee that something is compatible. The same is true here. You can always show there is a vulnerability, but you can never guarantee there are other vulnerabilities. It becomes one of an asymptotic approach, where you’ve verified so much that if there is a problem it’s going to be really rare and hard to get to. Beyond just the simulation, the insertion of features into a chip that can do analysis to minimize the possibility of a buried Trojan is, in fact, a key part. The other key part is on the incoming IP. How do you verify the IP you’ve got does not have Trojans in it and who do you trust. Do you trust your IP vendor? Do you trust some kind of simulation that goes through rigorous verification of that IP?”This is becoming a huge issue across the industry, because IP tracking is getting more convoluted as designs become more heterogeneous to deal with the increase in different types of data.“There are a lot of people getting into whole system architectures,” said Ranjit Adhikary, vice president of marketing at ClioSoft. “There are companies with a lot of PDKs, but you aren’t sure which PDKs are being used and you don’t know where the documentation is. This is a big mess. You don’t even know if IP went to tapeout in silicon or how much was paid for it.”That, in turn, has an impact on security. “There is no perfect solution when it comes to security,” Rhines noted. “Nothing gives you 100% certainty. But there are tests you can run. You can put intelligent features into the chip that look at the data flow and look for unusual sequences and put up a flag when an unusual sequence is executed, and possibly block the execution when a suspicious circumstance occurs. Products we’ve tested in the past merely flag unusual things going on in the system, and it’s up to them to look into it.”

2019-01-14 00:00 阅读量：1143

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ROHM Semiconductor

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TPS63050YFFR	Texas Instruments
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Texas Instruments

IPZ40N04S5L4R8ATMA1

Infineon Technologies

ESR03EZPJ151

ROHM Semiconductor

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ROHM Semiconductor

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