The networking and communications industry service providers — mobile, IoT, Internet, cable, and telecom technologies — are combining into a “converged network” because of the common infrastructures being implemented.

Things are changing dramatically in the world of these converged networks.

Not long ago, the cloud was the place all the data traveled, with huge quantities moving back and forth through the system. If you operated a mobile device, the processing of your data took place in a location far from that device. That’s just the way it worked.

It wasn’t such a problem when the demands were smaller and more manageable. The various operations worked fairly well, for the most part. But today’s requirements make the device-to-cloud setup increasingly inadequate, the remnant of a fast-disappearing era.

Challenges of a cloud-based architecture
There are several reasons for this, but three stand out in particular. First, the cost of transferring all that data is prohibitive. Second, the user exposes the data to excessive risks by constantly sending it to the cloud and back — it becomes vulnerable to interception by third parties.

The third issue is latency, an ever-present problem in a strictly cloud-based environment. There’s always a time lag when data goes to or from the cloud. Sometimes that gap is negligible, causing little to no problem. But in telecom, latency is a serious issue and the need to minimize it grows all the time as devices become increasingly sophisticated.

Moving processing to the network’s edge
These challenges have made Multi-Access Edge Computing (MEC) computing increasingly important. The edge is that point closest to the device in which processing occurs. Before the installation of smart nodes at the edge of mobile networks a few years back, the tower itself was the telecom edge. But as MEC technology progresses, the edge grows closer and closer to the device. In fact, the use case now defines where the edge should be in any given instance. The edge can still be the tower, but it can also be the central office, the autonomous vehicle or a remote oil rig.

The results of having the processing near the device are often dramatic. The device operates faster and can be considerably “smarter,” able to make decisions without having to receive data from the cloud first.  MEC is more economical, too, because it doesn’t entail a constant migration of data offsite and back again. You enjoy superior performance, a greater variety of functions for a lower operating cost.

More cost-effective, more functional
There are a host of applications in which edge computing improves cost and function —– for example, in the Internet of Things (IoT). An IoT environment with its superabundance of data would be clumsy and unworkable if it depended solely upon the cloud.

Many other applications benefit from processing data at the edge, chiefly, those in which bandwidth is a concern. Two good examples are virtual reality and drone controls. Both require low latency and the handling of voluminous data.

The reduced latency afforded by edge computing makes a major difference in so many applications. The need for low latency may be greatest in driverless vehicles, where split-second decisions associated with traffic feedback are critical.

The first order of business is getting the word out because edge computing is still relatively new on the market. There’s an ongoing need for education in the realm of converged networks. Communication service providers need to know, for example, how the edge can change their infrastructure into smart networks that meet high-capacity 5G requirements.

The sooner people learn about processing from the edge of the network, the sooner they can reap the many benefits.

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