Quantifying
the impact of
edge computing
on mobile applications

Cloud computing has been with us now for over a decade. And it's helping countless organizations transform their operations, scale and innovate while optimizing costs. But it's not the perfect fit for every use case. An emerging class of applications demands ultra-low latency, high bandwidth and mission-critical reliability. This requires processing data as close to users and devices as possible. Welcome to mobile edge computing (MEC).

The impact of edge computing on mobile applications could open up a whole new world of business productivity and outstanding user experiences.

MEC is a variation on the cloud theme. The difference is that instead of sending data back and forth to centralized data centers that may be located hundreds or thousands of miles away, most of the processing happens at the edge of the network. In effect, you're bringing the power of cloud computing to the edge—whether that's in smart factories, hospitals, telecom base stations or other locations. Servers, storage, Internet of Things (IoT) devices, edge gateways and network elements are typical components. But it's at the application layer where the fun happens.

Mobile edge computing refers specifically to the edge of a mobile network. But in fact, many other points where data is generated and consumed can be described as an “edge location.” These include local data centers, and devices such as routers, Wi-Fi access points and switches, i.e., the so-called device edge. That's why many organizations now refer to the technology as "multi-access edge computing."

What's not in any doubt, however, is the market potential of edge computing. It's expected to grow at a compound annual growth rate exceeding 42% over the next few years, topping $23 billion by 2028.

Edge computing on mobile applications works for several reasons. Benefits include:

• Latency: Also known as the amount of time it takes data to go from A to B, latency can have a major impact on the user experience for apps like online gaming and even voice assistants. Because data has far less distance to travel, lag is significantly reduced.
• Bandwidth: With edge computing, most of the heavy lifting is done at the edge, reducing the bandwidth needed between cloud data centers and IoT devices at the edge. This can lower costs, improve performance and support high-bandwidth apps, such as artificial intelligence-powered software.
• Privacy and security: There are several potential benefits in this area. Data has to travel shorter distances, so there are fewer opportunities to intercept it. It's also distributed across multiple remote sites, which reduces the risk of a mega-breach.
• Lightweight devices: Whether we're talking about end-user smartphones and tablets or corporate IoT endpoints, edge computing enables more processing to be done at the edge. That could make devices lighter, reducing costs and extending their battery life.

The mobile network may be just one of many access points for edge computing. But it's one of the most exciting when you consider the impact of edge computing on mobile applications. The low latency, enhanced reliability and support for greater device density 5G could offer may be a "force multiplier" for edge computing on mobile applications. That means speeds many times faster than 4G, better support for high-bandwidth applications, improved energy efficiency and resilience, and even enhanced security.

The result is more opportunities to deliver innovative use cases for edge computing on mobile applications, driving improved productivity, cost efficiencies and enhanced user experiences.

At the heart of the value proposition for mobile edge computing and 5G are the IoT devices that collect data and then act on analysis of this data performed almost instantly at the network edge. Because compute processing is done at the edge rather than the devices themselves, their energy requirements can be lower.

Quantifying the impact of edge computing on mobile applications isn't easy. In fact, there's an almost limitless range of use cases. Some of those that eventually dominate over the coming years may not even have been dreamed up yet. Here are some examples:

The smart factory will come of age thanks to edge computing. Industrial equipment fitted with smart sensors could monitor local conditions and make autonomous decisions to optimize production on the factory floor and reduce the risk of malfunction and safety issues.

Edge computing can power intelligent robotic customer assistants in branches, or facial recognition and other services at ATMs. Local data storage will suit the sector's strict regulatory requirements for data privacy and security and help to minimize data transport costs.

Connected patient monitors could analyze real-time data on the fly to notify clinicians of any serious deterioration in health, and even suggest diagnoses. Mobile edge computing powered by 5G in ambulances could help first responders with diagnoses and send vital health data back to hospitals to prepare doctors for incoming arrivals.