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More computing is happening on edge devices to handle the information overload

By 2020, an average internet user will use 1.5GB of traffic a day, and daily video traffic will reach 1PB, Intel predicts. A huge amount of data will be generated by autonomous vehicles, mobile devices, and internet-of-things devices.

Every day, more information is being collected and sent to faster servers in mega data centers, which analyze and make sense of it. That analysis has helped improved image and speech recognition and is making autonomous cars a reality.

Emerging superfast data networks like 5G — a melting pot of wireless technologies — will dispatch even more gathered information, which could stress data centers. Servers are already being redesigned to handle more data, and throughput technologies like Gen-Z and fiber optics will reduce latency.

At Mobile World Congress this week, computing on the edge was a big topic among infrastructure providers. Edge computing involves light processing on intermediary servers or on the edge of the networks. This type of computing can lead to faster responses for mobile services, without putting stress on servers in the core network.

Edge computing can also provide instant analytics to ensure the junk information is discarded and only useful information reaches servers on the core network. Edge computing is also emerging for virtualization, which slices loads of data in smaller packages rerouted to the right servers to be handled.

At MWC, many companies showed products and shared new ideas for computing on the edge. Most vendors had a common goal: to better control the flow and make better sense of data, especially with more data being collected by IoT devices.

Hewlett Packard Enterprise showed off its latest generation of IoT servers called Edgeline, similar to the company’s Proliant servers but slimmed down. The servers sit on the edge and are able to analyze data before sending them to core servers in data centers. The servers can virtualize data packets on the edge, which then makes better use of computing resources.

For example, the Edgeline servers can handle mobile computing tasks, like responding to Facebook posts or search requests, on the edge. More intense data tasks, like image recognition, can be routed back to the centralized data center network, which handles machine learning tasks.

Nearby, Dell was showing off its Edge Gateway 3000 servers for multiple IoT applications. The servers can analyze data at the point of collection and dispatch them to the data center. These servers use Intel’s latest Atom chips, which have up to 16 cores.


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