Technologent Edge Computing and Internet of Things

A Look at Use Cases for Edge Computing

Technologent Edge Computing and Internet of Things

The rapid growth of the Internet of Things (IoT) is driving increased adoption of edge computing — a network design model in which computing resources are placed at the network’s edge in close proximity to data-collection sources. Gartner analysts say 70 percent of the organizations they surveyed recently plan to make edge computing part of their infrastructure plans by the end of 2019.

This a significant shift away from today’s data center/cloud model in which almost all data processing occurs at a large, centralized core. However, the process of moving data to and from a data center for analysis doesn’t support time-sensitive applications where latency of even milliseconds is unacceptable.

With IoT projects involving data inputs from thousands or even millions of devices, organizations need a way to eliminate latency barriers between data sources and processing power. The edge computing model aims to reduce such delays by putting processing resources a single hop away from devices and users.

While edge computing goes hand-in-hand with IoT initiatives, there are many industries that can benefit from this model:

Industrial IoT: Manufacturing, logistics, oil and gas, transportation, energy/utilities, mining and metals, aviation and other industrial sectors typically depend on significant machinery, equipment and devices. Edge computing supports data collection and analysis for predictive maintenance to identify potential breakdowns before they impact production. This can extend the life of equipment, improve worker safety and maximize asset utilization.

Smart Building Services: Device-to-device communication enables a wide range of building automation solutions. Locally processed data can be used to orchestrate and optimize essential services such as security, tracking, climate control, lighting, smart signage, access control and more.

Retail: Edge devices such as beacons can collect information such as transaction history from a customer’s smartphone and then target promotions and sales items as customers walk through the store. Rapid data analysis can also allow retailers to adjust digital signage to highlight merchandise, sales and promotions, and to design store layouts and product placement to improve the customer experience.

Financial Services: Edge data analysis can help financial services organizations identify and halt illegal or unusual activity. For example, rapid data movement supports User and Entity Behavior Analytics (UEBA) applications that track what users are doing and how data is moving, flagging and interrupting any unusual transactions. Banking institutions are also using edge principles to provide ATMs and kiosks with the ability to gather and process data, allowing them to offer a broader suite of features.

Healthcare: Hospitals, clinics and other facilities are dealing with vast amounts of patient data. Edge computing enables real-time access to critical information for faster diagnoses and improved care. Edge computing is also seen as a key enabler of telemedicine initiatives to provide care in hard-to-reach rural areas.

Edge computing won’t replace conventional data centers — in fact, it can improve them through “data thinning” at the edge of the network. By reducing the amount of data being transmitted back to the data center, edge computing reduces backhaul traffic and conserves bandwidth.

However, edge computing also creates new challenges due to the distributed nature of the architecture, and few organizations have the skill sets needed to effectively deploy and manage edge technology. If edge computing is on your radar for 2019, we invite you to meet with one of our infrastructure experts to discuss your objectives.

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