Three-layer IoT edge system cake: Add specialized hardware, bake at low latency
“Internet of things” edge devices are causing quite a few headaches for technology vendors and businesses alike. Their whole selling point — intelligent, real-time decision-making at the edge of computing networks — is defeated by the latency of moving data back and forth to a cloud or physical data center for analytics. But edge devices can’t hack all the compute work themselves. Will edge systems connecting primary, secondary and tertiary data levels with low latency evolve to solve this snafu?
“The software and the devices need to be a single unit. And for the most part, they need to be designed by vendors — not by individual IT teams,” said Wikibon Inc. analyst Neil Raden (@NeilRaden). Raden and several others debated what a workable edge system will actually look like during a special Wikibon Research Meeting.
Most IT personnel are out of their depth in the minutiae of edge devices, according to Raden. For one thing, edge sensors collect data in a manner and for a purpose that are both unprecedented. Unlike virtually all data in any given data lake today, sensor data does not find its way into an analytics model after first fulfilling some wholly different role.
“Sensor data is really designed for analysis; it’s not designed for record keeping,” Raden said. This presents obvious benefits for tailoring models; but there are also challenges to corralling and organizing copious sensor data. “The retention and stewardship of that requires a lot of thought,” he added.
In the long chain of distributed data from edge device to cloud, there are not only complex latency and compute problems to solve; there are also thorny sovereignty and ownership questions, according to Dave Vellante (@dvellante), Wikibon chief analyst. “There are significant IP ownership and data protection issues. Who owns that data? Is it the device manufacturer? Is it the factory, etc.?” Vellante asked.
These and other unsolved mysteries led Maribel Lopez, founder and principal analyst at Lopez Research LLC, to recently describe the state of edge device as “an absolute disaster.” Its problems are so varied, there is no telling where the solutions will come from, Lopez said in a recent interview on theCUBE, SiliconANGLE Media’s mobile live streaming studio. “The IoT camp, I think, is a wild card for everybody right now,” she said.
Indeed, the “solution” may not be possible without scrapping all legacy systems and building from scratch, according to Wikibon analyst George Gilbert (@ggilbert41, pictured, center). Retrofitting edge devices and analytics into existing systems may prove impractical or impossible. Some advanced research on the edge coming from places like the UC Berkeley AMPLab, birthplace of the Apache Spark big data processing engine, calls for a deep infrastructure overhaul, Gilbert added.
“They’re saying we have to throw everything out and start over for secure, real-time systems, that you have to build from the hardware all the way up,” Gilbert said.
Earlier this year, Berkeley launched the RISELab (Real-Time Intelligence with Secure Execution) to improve the ability of machines to make intelligent, real-time decisions.
