Ubiquitous Smart Devices and the Coming Age of Edge Computing
Edge computing is on the way. Are you prepared for the dawn of this analytics-driven vision that combines advances in AI and networking to create more powerful localized systems?
- By Brian J. Dooley
- April 27, 2020
Edge computing is on track for significant development this year, and these changes will have important repercussions in infrastructure, networks, and analytics. That’s why, among all the other priorities you are balancing, you’ll want to keep your eye on edge computing developments this year.
Edge computing brings processing out to devices or gateways on the network. The basic concept is driven by the idea that some types of processing must be performed with extremely low latency to feed processes such as local analytics, robotic functions, and sensor operation. Powerful edge devices and gateways can compress data for transmission to the cloud, perform preprocessing, or handle and coordinate autonomous tasks without access to a central computer.
Because of these capabilities, edge computing is closely related to the growing development of the Internet of Things (IoT) and the rollout of 5G mobile networks. For analytics and data, there will likely be significant new opportunities and challenges. Supporting infrastructure must be put in place, and there will be new requirements for security and new models for processing IoT data.
Computing as close as possible to the point of use has always been important for applications requiring low-latency data transmission, very high bandwidth, or powerful local processing capabilities -- particularly for machine learning (ML) and other analytics.
One of the leading current uses is for autonomous vehicles, which need data from the cloud. If access to the cloud is denied or slowed, they must be able to continue to perform; there is no room for latency. The amount of data produced by all sensors on a vehicle is prodigious and must not only be processed locally, but anything sent up to the cloud must be compressed and transmitted on an as-needed basis to avoid overwhelming available bandwidth and taking precious time. IoT applications in general are important drivers of edge computing because they share a similar profile.
Edge computing is growing a portfolio of use cases that include autonomous devices, industrial robotics of Industry 4.0, smart home devices, AR/VR, telco functions, AI and ML, medicine, and finance. In each of these areas, it is possible to find cases where minimal latency and massive local processing can be of advantage. However, analysts see this going much further—and many corporations agree.
State of the Edge
Because it is seen as a significant new technology, many companies have jumped on the edge computing bandwagon. Progress is slow and the needed technologies are not yet in place, but limited opportunities can be found in nearly every area.
The State of the Edge report estimates that over $700 billion in cumulative capital expenditure will be spent over the next decade on edge infrastructure and data centers. According to the 2019 State of IT report by Spiceworks, 32 percent of organizations with over 5,000 employees already use edge computing. The 2019 Forrester Analytics Global Business Technographics Mobility Survey found that edge computing was being planned by 57 percent of decision makers. Equally optimistic predictions have been made by numerous analysts. However, the edge computing we have today bears little resemblance to the future envisioned in this concept—a future of autonomy, ubiquitous AI, and smart devices everywhere.
Edge computing is distributed, decentralized computing that puts significant power proximate to the end-user location. As such, it is a natural evolution in increasing computer power and mobility. The big change will come when infrastructure concepts are standardized with available software in place, 5G networks reach full operation and are available globally, standards are produced for IoT components, and costs begin to come down so that the Internet of Things itself begins to mature.
Because this is an area of high expected growth, major industry vendors such as IBM, Cisco, Oracle, Microsoft, Amazon, Dell, Hewlett-Packard Enterprise, SAP, and many others are venturing into the infrastructure area, hoping to gain a piece of a rapidly growing pie.
This is exciting stuff. Many analysts consider the year 2020 to be critical in moving edge computing further along the path to realization. This is because of the growth of 5G networking, increased expansion of IoT, growth of use cases, and increased attention (for example, due to high visibility of driverless cars)—along with a gradually growing understanding of what the 5G network might accomplish. Much is not yet known; current implementations tend to be highly proprietary and somewhat limited. This means that replication of successful cases is far more difficult.
Nonetheless, edge computing is certainly on the way and it is important to prepare for the dawn of this new future. It is an analytics-driven vision that combines recent advances in both AI and networking to create more powerful localized systems.
Brian J. Dooley is an author, analyst, and journalist with more than 30 years' experience in analyzing and writing about trends in IT. He has written six books, numerous user manuals, hundreds of reports, and more than 1,000 magazine features. You can contact the author at firstname.lastname@example.org.