What is Edge Computing?
If you are an engineer or simply involved in improving the performance of a manufacturing or logistics activity, edge computing is definitely the technology to consider. It has the potential to give you better insight into your line operations, as well as the ability to make faster and more accurate decisions.
As edge devices and sensors lumped together under the common denominator “Internet of Things” (IoT) generate more data and require more network and cloud resources, two issues arise:
- Bandwidth is limited and transferring large amounts of data becomes expensive.
- Round-trip time, or latency, slows down decision-making for time-critical operations.
At the same time, factory-installed devices, including smart cameras and high-performance barcode scanners, are acquiring more and more onboard computing power and consequently generating more and more data. By moving data processing closer to the data collection devices, i.e. at the edge, you can eliminate the latency of sending data to the cloud and waiting for instructions to return. reduce network congestion and increase reliability.
What are the 5 Benefits of Edge Computing?
Edge computing is developing into a megatrend and an indispensable element of modern IT infrastructures. The database specialist Couchbase names the five most important reasons for this.
IT goes to the periphery: Networked mini data centers on-site enable a multitude of new application and deployment scenarios, be it in digital cities (smart cities), in real-time gaming, or in the Internet of Things (IoT). With edge computing, IT is taking the next big development step after cloud computing. Newshoth analyzed the five key benefits:
1. Availability and Stability
Edge Computing reduces dependency on always-on Internet connections. Work can continue at the edge even in the event of network outages or failures, even offline if necessary. This increases the stability and availability of computing and storage resources.
2. Speed and Latency Tolerance
Latencies are a critical factor in many applications, such as the Internet of Things. Even short-term delays can lead to outages or failures there. With edge computing, there are no latency-critical data transfers between the edge and the data center, and latency times are reduced to fractions of a millisecond.
With edge computing, personal or business-critical data no longer has to be processed or stored in the cloud. This makes it easier to meet security and compliance requirements. At the same time, edge computing leaves open the option of using cloud resources for aggregated data that is not security-critical.
Along with 5G, edge computing opens up new application options on mobile devices. Only the speed of 5G and the latency tolerance and reliability of edge computing make mobile scenarios such as the use of autonomous vehicles possible.
Since a large amount of data is processed and stored on-site, edge computing drastically reduces network usage and therefore bandwidth requirements. The costs of this fall accordingly and are easier to calculate at the same time.
“Edge computing combines the scalability and on-demand capabilities of the cloud with the speed and resiliency of on-premises data centers,” said Paul Salazar, senior director for Central Europe at Couchbase. “This combination places great demands on control and management software, but also opens up a host of new application possibilities.”
In concrete terms, advanced computing is already widely used today. Many companies use it in very diverse fields, encompassing both aeronautical or automotive design, the optimization of transport networks, and the development of new drugs.
At present, three major patterns of use of edge computing have already emerged. The first of these models is to deploy edge computing in remote offices (for example, this is already the case with Walmart or Starbucks stores). The second of these models applies to telecom operators, who deploy their radio network over several layers of the infrastructure for mobile computing, and finally, the third concerns the use of IoT and other peripherals in the enterprise ( such as in manufacturing plants equipped with sensors).
It should be noted, however, that setting up these “supercomputers” requires significant technical programming skills, and it is essential to have undergone specialized training in IoT to master them.