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Connected devices push business to the edge (edge computing architecture, that is)

 Internet-connected devices have put a strain on enterprise networking. Edge computing architecture could alleviate some strain.

Connected devices continue to proliferate, each one ratcheting up the pressure on IT infrastructure.

According to analyst firm Gartner, there could be 20 billion Internet of Things (IoT) devices by 2020, ranging from connected cars to virtual reality-enabled headsets to refrigerators and oil rigs outfitted with sensors that communicate data.

Data from IoT-connected devices can indicate whether a refrigerator needs service, or it might give a connected car turn-by-turn directions to a movie theater where the driver has bought tickets for a 7:30 show. But they also generate massive amounts of data and execute processes that need to take place in milliseconds.

These processes may stall, however, if they undergo round-trip data transmission to cloud-based data centers. Often located miles away from the devices, applications and data they handle, cloud-based data centers create performance issues for high-bandwidth applications and devices. For processes that must take place in fractions of a second, latency obstacles can thwart speed and functionality.

“As the volume and velocity of data increases, so too does the inefficiency of streaming all this information to a cloud or data centre for processing,” wrote Gartner principal research analyst Santhosh Rao in an analysis of the impact of edge computing on infrastructure.

“In these situations, there are benefits to . . . placing [decentralized computing power] closer to the point where data is generated — in other words, to pursuing edge computing,” Rao wrote.

Edge computing architecture places high-performance compute, storage and network resources as close as possible to end users and devices. This arrangement reduces the burden of data transport to the cloud, decreases latency and increases locality.

According to BI Intelligence data, IoT devices connected to edge computing models are due to explode, from a mere 570 million in 2015 to 5.6 billion devices in 2020.

Bringing data to the edge

The ability to move computing processes to the edge yields real-world benefits. Just consider this kind of scenario with IoT and collaboration technologies transmitting data fast and furious in the manufacturing industry.

Italtel USA, a systems integrator, uses connected devices to monitor and control those trying to gain physical entry to manufacturing production lines, said Camilio Ascione, strategic alliance manager and chief technology officer at Italtel. The plant area is restricted to users with access privileges.

By building application programming interfaces (APIs) on top of its intent-based networking architecture, Italtel can use the network to verify user identity.

“It’s very dangerous to have someone in there who shouldn’t have access,” Ascione said.

If a user wants to gain access to the restricted area via an RFID-enabled badge, his or her identity is then sent to Italtel’s networking management console, Cisco DNA Center. Identity verification switches on an IoT-enabled surveillance camera to further identify the individual and also initiates a conversation via a chatbot, or automated digital assistant, which communicates via text or voice, with Cisco Webex Teams.

If the individual is denied entrance to the area, the chatbot can send an alert. Humans, who also manage access to the production line, can intervene and determine whether the individual should gain access or whether there may be a security risk requiring the production line to be shut down.

Edge computing architecture for bandwidth-hungry connected devices

Securing a production line involves numerous high-bandwidth applications, devices and data that can tax the network. The volume and velocity of the data will require edge computing capabilities.

“These [interactions] are very dynamic and very fleeting,” said Thomas Bittman, vice president and distinguished analyst at Gartner, at a conference on data center infrastructure, but today, the data is moving too quickly to be useful. “Business moments are being missed because we can’t capture them fast enough.”

Edge computing architecture could accommodate that ephemerality, dynamism and need for real-time insight.

According to Bittman, edge computing is going to become necessary to support these connected devices—and business needs—in the future. Edge computing and IoT will evolve in tandem.

“In the next few years,” Bittman predicted, “you will have edge strategies—you’ll have to.”

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Lauren Horwitz

Lauren Horwitz is the managing editor of Cisco.com, where she covers the IT infrastructure market and develops content strategy. Previously, Horwitz was a senior executive editor in the Business Applications and Architecture group at TechTarget;, a senior editor at Cutter Consortium, an IT research firm; and an editor at the American Prospect, a political journal. She has received awards from American Society of Business Publication Editors (ASBPE), a min Best of the Web award and the Kimmerling Prize for best graduate paper for her editing work on the journal article "The Fluid Jurisprudence of Israel's Emergency Powers.”