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Thinking about Intel’s announcement on Friday that it will acquire Wind River Systems, it occurs to me that this move syncs up nicely with a trend that I feel is beginning to surface: a global network of sensors of various types (call it the Grid) to complement the Web. But the connection isn’t obvious; so let me explain.

The press release from Intel emphasized Wind River’s embedded-software development and testing tools. Those are only a part of its product portfolio – its main claim to fame over the last two decades has been its proprietary real-time operating system/RTOS, VxWorks (it also has a Linux OS with real-time options). So Intel is buying not only software for development of products such as cars and airplanes that have software in them; it is buying software to support applications that must respond to large numbers of inputs (typically from sensors) in a fixed amount of time, or else catastrophe ensues. Example: a system keeps track of temperatures in a greenhouse, with ways to seal off breaches automatically; if the application fails to respond to a breach in seconds, the plants die.

Originally, in the early development of standardized Unix, RTOSs were valued for their robustness; after all, not only do they have to respond in a fixed time, but they also have to make sure that no software becomes unavailable. However, once Open Software Foundation and the like had added enough robustness to Unix, RTOSs became a side-current in the overall trend of computer technology, of no real use to the preponderance of computing. So why should RTOSs matter now?

What Is the Grid?

Today’s major computing vendors, IBM among the foremost, are publicizing efforts to create the Smart Grid, software added to the electrical-power “grid” in the United States that will allow users to monitor and adapt their electricity usage to minimize power consumption and cost. This is not to be confused with grid computing, which created a “one computer” veneer over disparate, distributed systems, typically to handle one type of processing. The new Smart Grid marries software to sensors and a network, with the primary task being effective response to a varying workload of a large number of sensor inputs.

But this is not the only example of global, immediate sensor-input usage – GPS-based navigation is another. And this is not the only example of massive amounts of sensor data – RFID, despite being slow to arrive, now handles RFID-reader inputs by the millions.

What’s more, it is possible to view many other interactions as following the same global, distributed model. Videos and pictures from cell phones at major news events can, in effect, be used as sensors. Inputs from sensors at auto repair shops can not only be fed into testing machines; they can be fed into global-company databases for repair optimization. The TV show CSI has popularized the notion that casino or hospital video can be archived and mined for insights into crimes and hospital procedures, respectively.

Therefore, it appears that we are trending towards a global internetwork of consumer and company sensor inputs and input usage. That global internetwork is what I am calling the Grid. And RTOSes begin to matter in the Grid, because an RTOS such as VxWorks offer a model for the computing foundations of the Grid.

The Grid, the Web, and the RTOS

The model for the Grid is fundamentally different from that of the Web (which is not to say that the two cannot be merged). It is, in fact, much more like that of an RTOS. The emphasis in the Web is of flexible access to existing information, via searches, URLs, and the like. The emphasis in the Grid is on rapid processing of massive amounts of distributed sensor input, and only when that requirement has been satisfied does the Grid turn its attention to making the resulting information available globally and flexibly.

This difference, in turn, can drive differences in computer architecture and operating software.  The typical server, PC, laptop, or smartphone assumes that it the user has some predictable control over the initiation and scheduling of processes – with the exception of networking. Sensor-based computing is much more reactive: it is a bit like having one’s word processing continually interrupted by messages that “a new email has arrived”. Sensors must be added; ways must be found to improve the input prioritization and scheduling tasks of operating software; new networking standards may need to be hardwired to allow parallel handling of a wide variety of sensor-type inputs plus the traditional Web feeds.

In other words, this is not just about improving the embedded-software development of large enterprises; this is about creating new computing approaches that may involve major elaborations of today’s hardware. And of today’s available technologies, the RTOS is among the most experienced and successful in this type of processing.

Where Intel and Wind River Fit

Certainly, software-infused products that use Intel chips and embedded software are a major use case of Intel hardware. And certainly, Wind River has a market beyond sensor-based real-time processing, in development of embedded software that does not involve sensors, such as networking software and cell-phone displays. So it is reasonable for Intel to use Wind River development and testing tools to expand into New Product Development for software-infused products like audio systems; and it is reasonable for commentators to wonder if such a move trespasses on the territory of vendors such as IBM, which has recently been making a big push in software-infused NPD.

What I am suggesting, however, is that in the long run, Wind River’s main usefulness to Intel may be in the reverse direction: providing models for implementing previously software-based sensor-handling in computing hardware. Just as many formerly software-only graphics functions have moved into graphics chips with resulting improvements in the gaming experience and videoconferencing, so it can be anticipated that moving sensor-handling functions into hardware can make significant improvements in users’ experience of the Grid.

Conclusions

If it is indeed true that a greater emphasis on sensor-based computing is arriving, how much effect does this trend have on IT?  In the short run, not much. The likely effect of Intel’s acquisition of Wind River over the next year, for example, will be on users’ embedded software development, and not on providing new avenues to the Grid.

In the long run, I would anticipate that the first Grid effects from better Intel (or other) solutions would show up in an IT task like power monitoring in data centers. Imagine a standardized chip for handling distributed power sensing and local input processing across a data center, wedded to today’s power-monitoring administrative software. Extended globally across the enterprise, supplemented by data-mining tools, used to provide up-to-date data to regulatory agencies, extended to clouds to allow real-time workload shifting, supplemented by event-processing software for feeding corporate dashboards, extended to interactions with the power company for better energy rates, made visible to customers of the computing utility as part of the Smart Grid – there is a natural pathway from sensor hardware in one machine to a full Grid implementation.

And it need not take Intel beyond its processor-chip comfort zone at all.

 
Wayne Kernochan