What is computing 'at the edge?'

Edge computing is driving the transformation of how data is being handled, processed, and transmitted from millions of devices worldwide. As the number of internet-connected devices continues to expand, the Internet of Things (IoT) is changing how edge-computing systems evolve. This will significantly reduce bandwidth costs for sending data over long distances and enable real-time applications to run more efficiently.

What is edge computing?
Edge computing is an innovative topology that localizes data analysis and storage at the network's edge nearest to the data generation source. This approach encompasses devices, networks, and enterprise applications, working in unison to expedite actionable insights, enhance data processing speed, and conserve bandwidth. By taking the computation and data storage parts of the puzzle and fitting them into place close to where devices live, gather, and transmit information, tasks are decentralized - making centralized servers less the focus and more of a backup.

This is particularly important for applications that depend on real-time connectivity because latency issues can affect performance. The exponential growth of IoT devices has led to the generation of enormous amounts of data, causing bandwidth costs to rise sharply. By installing edge-computing hardware and services to serve as a local source of processing and storage, you can cut costs and improve speed. An edge gateway can gather data from an edge device, process it in real-time to issue actionable commands, or parse and forward only required data through the cloud, reducing bandwidth needs.

Edge devices can include:

• IoT sensors
• Field employee notebooks or smartphones
• Security cameras
• Internet-connected appliances
• Edge gateways

AI and the edge
In the past, cloud and AI technology aimed to speed up innovation and enable data-driven actions by extracting valuable information. However, the immense volume and intricacy of data generated by interconnected devices have surpassed the capabilities of existing networks and infrastructure.

Directly transferring all this data from devices to centralized data centers or the cloud leads to higher bandwidth usage and slower response times, making edge computing a more appealing alternative. Processing and analyzing data closer to its source minimizes the need for data to travel across networks, thus significantly reducing latency. Edge computing, particularly when paired with 5G networks, allows for a swifter and more extensive data analysis, resulting in better insights, quicker responses, and enhanced user experiences. 

For example, consider facial recognition. A device scans a person's face and then must send the image to run the facial recognition algorithm through a cloud-based service. Edge computing allows the algorithm to run locally on an edge server or gateway, cutting the time for returned results to a fraction of what it took before. Edge computing is the future of virtual and augmented reality and will be the driving force behind the adoption of building automation, self-driving cars, and smart cities.

Data security at the edge
The final problem to solve is security at the edge. Devices can be easier to hack than systems, and bad actors are already discovering how to infiltrate entire networks through devices at the edge. As IoT device adoption continues to grow exponentially, IT departments must understand and take action to protect against the potential security issues around these devices, securing systems by ensuring that data is encrypted. Instituting zero-trust controls, VPN tunneling, and wider firewalls can help protect data at the edge.

Edge computing empowers organizations to harness the vast amount of data generated by interconnected devices, introducing a wealth of untapped possibilities. It offers a gateway to enhance operational productivity while ensuring quick, dependable, and unified experiences for clients. Optimal edge computing strategies can supercharge performance, keep workloads updated, and comply with corporate policies.