Just like the universe, the Internet of Things (IoT) is expanding every day. An estimated 22 billion devices will be connected to the internet by 2025. And all those new devices, sensors, and computers will be generating, processing, and sharing a lot of data. This massive amount of IoT data demands swift processing and substantial storage space and colocation. Edge data centers are critical backbone infrastructures 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 the IoT sensor data.
What is Colocation?
Using colocation is sort of like renting an apartment for data. A colocation facility leases space, power, cooling, network solutions, and security to many customers at once, while each customer brings their own “furniture,” such as the IT equipment and servers. In the last decade, colocation has evolved from a convenient option for companies to store data off-site before committing investment to build their own data centers to a more robust and advantageous solution to in-house data centers. The proliferation of colocation facilities is a powerful force for IoT growth due to colocation’s capability to deliver reliable uptime, low-latency connections, cloud on-ramps to connect multi-cloud environments, and on-demand scalability.
Colocation for Closer Connections
In many applications of IoT, speed is the name of the game, and the speedy transfer of data relies on two major factors:
- The bandwidth between an IoT device and the network
- The device’s proximity to that network
Take self-driving cars for example. In San Francisco, several driverless vehicle companies have turned to colocation as they test their technology on the street in this urban center. The IoT data stream can quickly grow into a full-on flood with millions of sensors and live processing demands firing inside every car.
In nearby Sunnyvale, a colocation data center functions as a high-volume hub for driverless car sensor data, which can be securely processed to inform the controls of all other driverless cars in the same area. IoT sensors capture data on speed and direction utilizing GPS, vectors, and maps because these and more data points impact the decision-making of driverless cars. Each of these deterministic processes must be reviewed, analyzed, and processed by software – all this happening in real-time with the vehicle reporting back to the data center.
Suppose self-driving vehicles are going to some day populate roadways everywhere. In that case, they’ll need access to data centers with close connections and high throughput circuits to handle all the data they generate. Driving, after all, requires split-second decision-making, and that translates to extremely low latency data transmission. Distributed widely, colocation data centers allow driverless cars to always have a quick, close connection to other relevant IoT devices in a geographic area, similar to how cell phones connect to nearby towers as they travel.
5G Network for Speed
While proximity increases the speed at which IoT data is shared, the emergence of a 5G communication network 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 5G could potentially run 100 times faster. Many IoT devices connect directly to the public cloud, sending their sensor data there and receiving communications back. But issues arise when so many devices—potentially tens of billions in only a few years—are all transmitting data along hyper-speed 5G networks. Data congestion can slow IoT connectivity to a crawl 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 the ground, where IoT devices are located. Essential, speed-needy data functions take place close to the device or within a nearby data center, and subsequent data heads to the cloud either directly or via colocation direct cloud connects, where necessary. This hybrid computing process is often called fog or edge computing.
Colocation data centers aid fog computing by offering many points of low-cost space and secure protection for IoT data with an extra layer of connectivity to the cloud. Because colocation customers run their own hardware within the remote data centers, they have full control over the privacy of their IoT network of devices and the development testing environment. IoT devices connected directly to public cloud infrastructure have faced worrying security breaches, so security experts recommend keeping access to IoT devices limited to a private network. In a smart home, if the lightbulbs, fridge, and thermostat all link up through a public cloud, this is comparable to leaving the front door unlocked in terms of a hacker’s ease of entry.
Preparing for Rapid IoT Growth
With IoT devices proliferating so quickly, there is a growing need to rapidly scale up data infrastructure to incorporate significantly higher volumes. Companies that deploy IoT technology are poised to become more profitable as the number of connected devices and their critical functions become a larger part of our commerce and lifestyles, but they also risk becoming victims of their own success if they don’t react quickly to growth.
Colocation provides benefits to IoT on speed and security, and it also enables IoT data networks to expand rapidly by allocating more bandwidth, power, and space in little time. Market forecasters predict the colocation data center market to grow exponentially by more than 7 percent in each of the next five years. That would put the colocation market size at nearly $50 billion by 2027. Driving that growth is the expanding universe of IoT. The more we connect to each other and the world around us through IoT devices, the greater the need for colocation capacity to handle all the data that serves as the foundation of all IoT interactions.
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