The Inevitable Rise of Intelligence in the Edge Ecosystem
A new frontier is taking shape where smart, autonomous devices running data on 5G networks process information that can lead to near real-time insights enterprises need.
The implementation and adoption of 5G wireless, the cloud, and smarter devices is setting the stage for advanced capabilities to emerge at the edge, according to experts and stakeholders. Communications providers such as Verizon continue to flesh out the newest generation of wireless, which promises to offer more robust data capacity and mobile solutions. In brief, the edge has the potential to be a place where greater data processing and analytics happens with near real-time speed, even in seemingly small devices. On the hardware and services side, IBM, Nokia Enterprise, DXC Technology, and Intel all see potential for these converging resources to evolve the edge in 2021 in exponential ways — if all the right pieces fall into place.
The edge is poised to support highly responsive compute, far from core data centers, but Bob Gill, research vice president with Gartner, says the landscape needs to become more cohesive. “As long as all we have are vertical, monolithic, bespoke stacks, edge isn’t going to scale,” he says, referring to the differing resources created to work at the edge that might not mesh well with other solutions.
Gill defines the edge as the place where the physical and digital worlds interact, which can include sensors and industrial machine controllers. He says it is a form of distributed computing with assets placed in locations that can optimize latency and bandwidth. Retailers, internet of things, and the industrial world have already been working at the edge for more than a decade, Gill says. The current activity at the edge may introduce the world to even more possibilities. “What’s changed is the huge plethora of services from the cloud along with the rising intelligence and number of devices at the edge,” he says. “The edge completes the cloud.”
The focus of the evolution at the edge is to push intelligence to locations where bandwidth, data latency, and autonomy might otherwise be concerns when connecting to the cloud or core computing. With more autonomy, Gill says devices at the edge will be able to operate even if their connections are down.
This might include robots in manufacturing or automated resources in warehousing and logistics, as well as transportation, oil, and gas. Organizations will need some normalization of platforms and solutions at the edge, he says, in order to see the full benefit of such resources. “They’re looking for standardized toolsets and a way that everything isn’t a bespoke one-off,” Gill says. This could include using open source frameworks deployed to create solutions that can be tweaked.
Gill expects there to be move toward a standardized approach in the next five years. He says enterprise leadership should ask questions about ways the edge can help the organization achieve goals while also eliminating risk. “The c-suite should be saying, ‘What is the business benefit I’m getting out of this? Is it something that’s replicable?’”
Edge computing is becoming an integral part of the distributed computing model, says Nishith Pathak, global CTO for analytics and emerging technology with DXC Technology. He says there is ample opportunity to employ edge computing across industry verticals that require near real-time interactions. “Edge computing now mimics the public cloud,” Pathak says, in some ways offering localized versions of cloud capabilities regarding compute, the network, and storage. Benefits of edge-based computing include avoiding latency issues, he says, and anonymizing data so only relevant information moves to the cloud. This is possible because “a humungous amount of data” can be processed and analyzed by devices at the edge, Pathak says. This includes connected cars, smart cities, drones, wearables, and other internet of things applications that consume on demand compute.
