Like the universe, the Internet of Things (IoT) is expanding every day. By 2025, 22 billion devices are expected to be connected to the Internet. All of these new devices, sensors and computers will generate, process and share vast amounts of data. This massive amount of IoT data requires fast processing and a lot of storage space and hosting. Edge data centers are critical backbone infrastructure that will help support the IoT revolution. Data pools become data lakes and oceans, and data centers will need to process, analyze, and store all IoT sensor data.

What is colocation?

Using colocation is a bit like renting an apartment to get data. A colocation facility leases space, power, cooling, networking solutions, and security to multiple customers at the same time, while each customer brings its own "furniture" such as IT equipment and servers. Over the past decade, colocation has evolved from a convenient option that lets companies store data offsite before committing to investing in building their own data center, to a more powerful and profitable in-house data center solution. The proliferation of colocation facilities is a powerful driver of IoT growth, as colocation provides reliable uptime, low-latency connectivity, cloud on-ramp to multi-cloud environments, and on-demand scaling.

Colocation for tighter connections

In many applications of the Internet of Things, speed is key, and the rapid transfer of data depends on two factors:

1. Bandwidth between IoT devices and the network.

2. The proximity of the device to the network.

Take self-driving cars, for example. In San Francisco, several self-driving car companies have turned to colocation to test their technology on the streets of the city center. IoT data streams can quickly grow into a full-blown torrent, with millions of sensors and real-time processing demands in every vehicle.

In nearby Sunnyvale, a colocation data center acts as a high-capacity hub for driverless car sensor data that can be safely processed to inform control of all other driverless cars in the same area. IoT sensors utilize GPS, vectors, and maps to capture speed and direction data, as these and more data points influence driverless car decisions. Each of these deterministic processes must be reviewed, analyzed, and processed by software—all in real-time, with the vehicle reporting to the data center.

Suppose one day self-driving cars will populate roads everywhere. In this case, they will need access to data centers with tightly connected and high-throughput circuits to process all the data they generate. After all, driving requires instantaneous decision-making, which means extremely low latency for data transmission. Colocation data centers are widely distributed, allowing driverless cars to maintain fast, tight connections to other relevant IoT devices in a geographic area at all times, similar to how a cell phone connects to a nearby cell tower while driving.

5G network boosts speed

While proximity has increased the speed of IoT data sharing, the advent of 5G communication networks makes the speed equation even more important. The fastest 5G networks are expected to transmit data at least 10 times faster than 4G LTE. Some experts believe that 5G could operate 100 times faster. Many IoT devices connect directly to the public cloud, send their sensor data there, and receive communications. But the problem arises when so many devices -- potentially tens of billions in just a few years -- are streaming data over superfast 5G networks. Data congestion can slow IoT connections to a snail’s pace, like a traffic jam on a multi-lane highway.

Hybrid computing drives IoT data

Researchers have explored the benefits of moving cloud connectivity closer to where IoT devices are located. Important, speed-requiring data functions take place near the device or in a nearby data center, with subsequent data entering the cloud directly or via a hosted direct cloud connection (if necessary). This hybrid computing process is often referred to as fog or edge computing.

Colocation data centers help fog computing by providing a lot of low-cost space and security for IoT data, as well as an extra layer of connectivity to the cloud. Since colocation customers run their own hardware in remote data centers, they have complete control over the privacy of their IoT device network and development test environment. IoT devices that connect directly to public cloud infrastructure face worrying security vulnerabilities, so security experts recommend limiting access to IoT devices within private networks. In a smart home, if lightbulbs, refrigerators and thermostats are all connected via the public cloud, it's the equivalent of unlocking the front door in terms of how easy it is for hackers to get in.

Preparing for the Rapid Growth of the Internet of Things

With the rapid growth of IoT devices, there is a growing need to rapidly scale data infrastructure to accommodate larger capacities. As the number of connected devices and their critical functions become a larger part of our business and way of life, companies deploying IoT technology will become more profitable, but if they cannot respond quickly to growth, they also have the potential to become victims of their own success.

Colocation provides IoT with speed and security benefits, and it also allows IoT data networks to scale rapidly by allocating more bandwidth, power, and space in a fraction of the time. Market forecasters predict that over the next five years, the colocation data center market will grow exponentially by more than 7% each year. By 2027, the colocation market will reach nearly $50 billion. Driving this growth is the ever-expanding world of IoT. The more we connect to each other and the world around us through IoT devices, the more we need managed capacity to process all the data that underlies all IoT interactions.

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