The next evolutionary phase of IT infrastructure is the Internet of Things (IoT), particularly the edge platforms that will handle much of the data load from millions, nay billions, of connected devices.
A data ecosystem of this size and scope will not emerge in a day, however. So at this point in time, as we head into the last year of the decade, what state of development has the IoT edge achieved and what is likely to take shape in the coming year?
While the IoT is already churning out massive volumes of data, this is only the slightest fraction of what is likely to arise over the next decade. Virtually every thing that we see and touch, and perhaps even parts of our own bodies, will soon be generating continuous data streams to processing and storage elements on the edge and in centralized data facilities, where it will be parsed, analyzed, combined and otherwise manipulated – theoretically to the benefit of the connected public.
IoT Gathering Steam
According to Zebra Technologies, the average enterprise invested $4.6 million into IoT infrastructure over the past year, a 4 percent increase over 2017. About 84 percent of enterprises expect to complete their IoT implementation by 2021, although this is likely a misnomer. The IoT is not likely to be “complete,” probably ever, any more than current data center infrastructure is complete. Most likely, the expectation is that the IoT will have reached a sufficient stage of development in the next two years to begin making significant contributions to business models.
Perhaps a more interesting data point comes from CB Insights, which estimates that within two years, virtually every person on Earth will generate 1.5 GB of data per day. This will propel spending on IoT systems and services from less than $500 in 2013 to more than $1.7 trillion in 2019. By 2022, the firm expects edge infrastructure alone to draw more than $6.7 billion in spending.
Of course, edge technology consists of myriad categories and subcategories, all of which should empower a wide range of use cases – everything from smart appliances to smart cars to entire smart cities. If there is one overarching theme to this technological base, however, it centers on finding ways to process the enormous amount of data in the most efficient and effective manner.
One of the most fundamental technologies in this effort, not just in the IoT but virtually all data infrastructure, is artificial intelligence. Gartner predicts that tools like machine learning, neural networks and autonomous analytics and other applications should prove invaluable in getting data to the right place, analyzing it in the right context, and delivering insights to the right people. In many cases, these actions will have to take place in real or near-real time, such as when a self-driving car is making its way down the highway or a connected medical device is providing life-saving service to a patient.
At the same time, intelligent systems on the edge will have to determine for themselves what data to process locally and what should go to centralized facilities. Much of the edge will consist of micro data centers that deliver results quickly to connected devices, providing not only rapid response times but preventing centralized compute, storage and networking resources from becoming overwhelmed. To that end, the edge will require not just automation but a high degree of autonomy in which machines decide for themselves how to proceed under a wide range of circumstances.
Gartner also predicts the eventual transition from an intelligent edge to an intelligent mesh. This architecture will be much more flexible and responsive to IoT workloads and systems even as it becomes more complex. In this way, the IoT will foster greater connectivity between edge resources and even between endpoint devices themselves, essentially replacing today’s point-to-point solutions with a new layer of multipoint-to-multipoint fabrics.
Skills Gap
Clearly, this will drive demand for entirely new skill sets among the knowledge workforce even as many of today’s existing skills diminish. Once networks, for example, have the ability to provision and configure themselves, traditional admin responsibilities will fade while more strategic roles will gain in stature. IDC is already calling attention to the lack of skilled professionals capable of overseeing AI-driven processes, which will become a major problem given that most organizations are expecting a 90 percent success rate implementing AI on IoT infrastructure over the next two years.
While the popular conception is that AI functions entirely on its own with no human oversight, the fact of the matter is that virtually no intelligent solution will operate properly without a skilled data scientist telling it what to do. This means tomorrow’s IoT-facing enterprise will have one of three choices: Retain existing IT staff on the intricacies of data science, outsource intelligent operations to specialized providers, or begin experimenting directly with open source models.
To many, the last option is the most intriguing since it seems that much of the IoT will be based on open infrastructure. As Rocky Bullock, CEO at the Open Compute Project (OPC) Foundation, explained to Data Economy recently, open source will be crucial to the edge because, by nature, it will require broad collaboration across a sea of systems and platforms. To be sure, some proprietary solutions will take root, but even these will require broad interoperability with their surroundings if they are to have any hope of meeting the expectations that most users have of the IoT.
In this light, we can expect the development of open, interoperable standards across a wide range of technologies that drive the IoT, including intelligent, automated platforms. At the moment, much of this is happening piecemeal through organizations like the IEEE, OCP and the Telecom Infra Project (TIP). In time, however, it is reasonable to expect more comprehensive solutions to emerge.
The IoT will undoubtedly see continuous development across a wide range of functions, such as security, governance and the like, but the focus for the coming year will be to push today’s largely behind-the-scenes operations to the forefront of the digital economy. Once it becomes a service- and revenue-generator in its own right, rather than a mere extension of legacy infrastructure, we will safely be able to say that we live in a truly connected universe.
Arthur Cole writes about infrastructure for IT Business Edge. Cole has been covering the high-tech media and computing industries for more than 20 years, having served as editor of TV Technology, Video Technology News, Internet News and Multimedia Weekly. His contributions have appeared in Communications Today and Enterprise Networking Planet and as web content for numerous high-tech clients like TwinStrata and Carpathia. Follow Art on Twitter @acole602.
