One of the most hyped terms the last year has been the “internet of things”, abbreviated to “IoT”. IoT is essentially the vision that nearly everything is connected to the internet. This includes not just smartphones, tablets and PCs, but includes clothes, cars, appliances, light bulbs, door locks, thermostats, toys, etc. Whether you buy into Cisco’s 50B connected devices by 2020 or Intel’s 16B devices by 2015, it doesn’t matter- it’s a very large number. Compared with the few billion smartphones, IoT will make that market look small. With all these devices connected to networks, the current enterprise architectures will need a massive overhaul. Before rendering a hard and fast recommendation on what it needs to be, it’s important to suggest a framework for IoT. While I have written a detailed report for youhere (free), let me lay it out simply below.
Early frameworks for this visionary universe of ambient, sensor-enabled systems of systems are mostly focusing in on vendor-specific issues. They are either too narrowly scoped: sensors, Big Data analytics, data connectivity, transport and security, managing complex systems of systems in the field. Or they are too broadly scoped: ill-defined, and are overreaching to define too many attributes of these systems…attributes that have not yet been adequately envisioned.
The challenge is to start with end-to-end services delivery in mind, while leaving room for technology and market evolution and innovation-driven value over the next few decades. The concept of “Intelligent Systems INS -2.46%” is emerging as a way for today’s infrastructure vendors to create a useful market structure and compete in key components of these embryonic end-to-end services.
I propose this definition of Intelligent Systems:
- Internet connected: Adheres to standard Internet protocols as they evolve
- Intelligent: Runs user-mode applications
- Managed: Monitor and configure over the Internet
- Secured: Encryption and authentication for management and communications; threat and malware detection and resolution
- End-to-End: Consistent service interfaces span the ecosystem
I purposefully exclude some popular topics from the IoT definition:
- People vs. machines: focusing on this to the exclusion of M2M and IoT seems short-sighted.
- Native vs. cloud-based applications: this is an artificial distinction between user-mode apps running on a client device and user-mode apps running in a datacenter.
- Big data and analytics: Big Data and Analytics are following the path of Cloud as the next “must use” terms to describe products.
The impact of poorly coordinated standards across IS systems will be unneeded complexity and balkanization of vendor ecosystems and products—which directly translates into buyer confusion and stalled market development.
The stunning success of smartphones, followed by similar success for tablets, has pushed the standardization opportunities for next generation infrastructure into play for the top tier of visionary companies. For the most part, their postures seem somewhat hurried. Here are what the current players are doing:
- IBM Smarter Planet has identified relevant IoT real-world issues for vertical markets and has what looks like a large marketing and consulting effort aimed at vendors in those verticals.
- Cisco’s Internet Business Solutions Group is in the Internet of Everything (IoE) camp—IoT being, apparently, insufficient.
- Microsoft Intelligent Systems seems aimed at incremental Windows Embedded sales.
- Google GOOG +0.82% researchers are spread out through the IoT world, and they are funding other folks’ experiments.
- GE’s Minds + Machines initiative is a wildcard. GE is large enough to affect the direction of the industry, should they choose.
- IPSO Alliance (Internet Protocol for Smart Objects) formed in late 2008 to promote the use of IP in smart objects: sensors and other end-points.
- ARM talks evocatively of “wearable, ingestible, implantable” sensors as well as massive server installations.
- International M2M Council is a new, global trade association to connect vendors and adopters.
- HP M2M Solutions is focused on M2M communications and not yet focused on an integrated IS strategy.
- Qualcomm is in the IoE camp and is similarly focused on end-points and M2M communications without including the larger IS picture.
- IoT-A (Internet-of-Things Architecture), formed in 2009, is a European Lighthouse Integrated Project. We give them good marks on completeness of vision and being forward looking.
- Intel’s Intelligent Systems Framework (ISF) is a forward-looking framework for describing the baseline capabilities of, and interactions between, IS systems of systems. Intel INTC +0.88%’s scope is broad, but it is more focused than IoT-A.
As you can see, there is a lot of dispersed activity without a central point of control or standards. This is exactly why frameworks I’ve addressed above are important.
As you evaluate overlaying IS and Big Data analytics onto existing infrastructure—or the build-out of entirely new M2M and IoT infrastructure—it is critical to consider that this market will undergo massive change over the next decade:
- The sensor market will be a Darwinian stew of evolutionary experiments.
- New network and storage hierarchies will evolve to manage the accelerating inflow of increasingly rich data from growing sensor deployments.
- New datacenter technologies will come online to analyze and react to the sensor data flow in real-time.
Vendors will be vying for IoT, IoE, M2M, etc. to position themselves over the next couple of years. We recommend a couple of initial directions:
Tap into sensor innovation. Sensors are expendable and replaceable, especially considering the rapid increase in capabilities we expect through the end of this decade. Treat them as such and do not lock into long-term directions yet.
Focus on end-to-end basics for IS. Deploy intelligent, manageable, and secure intelligent systems that will absorb the data from and manage your sensor networks. Pay attention to emerging frameworks and standards. Stay flexible, but watch for increases in complexity that can result in management headaches and non-deterministic service behavior.
If you are looking for a deeper dive on this topic, you can read a detailed report here (free).