The shift to cloud computing has fundamentally transformed the way organizations design and implement their networks. Whether they’re using a public cloud, a purely private cloud, or a more complex hybrid cloud or multi-cloud deployment, companies have embraced the solution due to its versatility and scalability. The centralized nature of cloud architecture, however, has failed to resolve latency challenges imposed by the distance between data centers, where most data is collected and analyzed, and end users located closer to the edge of the network.
Edge computing framework, which pushes key data processing functions to devices and data centers closer to the edge of the network architecture where the data is actually gathered, has offered many companies a way out of the latency and “last mile” problem. Internet of Things (IoT) devices, smart devices capable of connecting to the internet and managing data, have the potential to further empower edge networks to deliver fast, responsive services. As these devices become more common, more companies will surely be looking for ways they can be incorporated into their edge computing framework.
Edge computing architecture is highly valued for its ability to process data on the outer edges of networks closer to where end users are located. The concept is simple enough to understand. Located processing workloads closer to users results in reduced latency, helping companies to deliver services faster. But all of this data has to be gathered by something. IoT devices on the network edge have the ability to collect tremendous amounts of data, both from the way they’re being used and from sensors passively collecting information from their environment. This data not only helps edge computing IoT devices operate more effectively, but it also allows companies to leverage big data analytics to gain meaningful business insights for a competitive advantage.
As engineering innovations have allowed processor manufacturers to build smaller, more powerful chipsets, IoT devices have become more powerful with each successive generation. Today’s devices are capable of processing more data locally, which means data can be gathered and analyzed on the network edge without having to transfer the bulk of it back to centralized cloud servers. Limiting the amount of data being transferred through the network can significantly reduce latency in the system, providing users with a faster, more responsive experience. Having that additional processing power on the network edge also opens up future possibilities. Newer devices could be optimized to leverage the processing power of existing devices around them to keep even more data and functionality on the edge, further increasing the functionality of edge computing framework.
The onboard processing and data collection capabilities of IoT devices also have the potential to extend the reach of existing cloud edge computing networks. Traditional, centralized networks require a great deal of time and expense to set up. Although edge data centers and portable micro data centers make it possible to extend network services cost-effectively, they are still a fixed location that can only extend the edge network so far. Portable edge computing IoT devices with enough processing power to function independently, by contrast, can be taken far beyond the reach of the network. While disconnected, they can continue to gather and process data locally to provide a high level of functionality for users. When the time comes to reconnect to the network, they can share accumulated data for additional processing and receive new information in the form of updates. This has been especially valuable for healthcare and manufacturing IoT devices, which are often required to operate in low-service areas well beyond the reach of existing networks.
In addition to gathering data on usage trends, edge computing IoT devices also provide an unparalleled level of visibility into what’s actually going on along the network edge. This is especially valuable for companies with extensive supply chains. Smart IoT sensors make it possible to identify where every shipped product or asset is located at any given time. They can also evaluate where processing needs are most intense and where specific services are actually being used. Rather than simply releasing products into the world and hoping to receive feedback about their performance in the form of follow-up surveys or other research, IoT devices can provide real-time, actionable data on how they’re being used and whether they’re meeting consumer needs.
Although most companies think of IoT devices in terms of their own edge network, the connectivity capabilities of these devices present exciting opportunities to extend functionality across networks. As 5G networks roll out in new markets over the next few years, IoT devices will have the ability to interact with a variety of overlapping networks and devices to empower mobile edge computing. One of the most notable edge computing examples is the way autonomous vehicles will gather, generate, and exchange data with other devices and smart city infrastructure to enhance safety and performance. Combined with strategically located edge data centers, the connectivity of IoT devices will enable companies to expand their network reach in new ways to deliver better, faster services.
It’s difficult to discuss the potential of edge networks without also highlighting the role of IoT devices. The processing power that allows these devices to function independently opens up a variety of opportunities for companies to develop new architectures that upend traditional ideas about how networks should be designed and deployed. With more IoT edge devices hitting the market each year, edge computing examples will surely become more common and innovative features of IT strategies.
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