The impact of edge computing in today's Internet of Things (IoT)

TechNews Writer
Mon Feb 20, 2023

Do you remember your first encounter with a large, heavy computer set? As devices became smaller, their processing and computing capacity increased dramatically. The emphasis has quickly shifted to cloud computing or "offsite storage," whereas data warehouses and server farms were once thought to be the best option for processing performance. Cloud computing has even inspired entire business models for SaaS companies such as Netflix, Spotify, and others. However, there are several drawbacks to cloud computing. The main issue with cloud computing is latency, which is caused by the distance between consumers and the data centers that host the services. As a result, edge computing, a new technology that brings computers closer to their users, was developed.

Instead of processing data in the cloud or in data centers, edge computing is a distributed IT architecture that brings computing resources as close as feasible to the data source. In the Internet of Things (IoT) ecosystem, the edge plays an increasingly crucial role, as evidenced by the sheer number of terminologies used. Far and close edges, thin and thick edges, as well as the network edge, are among them. Fog computing, which serves as a bridge between the edge and the cloud, is another. The phrase "edge continuum" describes how the necessary compute resources can be spread for optimal processing, from edge systems and devices to cloud and private data centers.

The far edge is infrastructure deployed in a location remote from cloud data centers but close to users: devices and sensors, as well as cell towers. The infrastructure deployed between the far edge and cloud data centers, closer to telecom central offices, is referred to as the near edge. Thin edge computing (also known as constrained edge computing) involves less processing at the point of sensor data collection. Thin edge frequently involves battery-powered sensors or devices used for applications that produce small amounts of data, such as tracking.

Data is traditionally produced on a user's computer or any other client application, and it is then transferred to the server via channels such as the internet, intranet, LAN, and so on, where the data is stored and processed. This is a tried-and-true method of client-server computing. However, due to the exponential growth in the volume of data produced and the number of devices connected to the internet, traditional data center infrastructures are finding it difficult to accommodate them.

According to a Gartner study, 75 percent of enterprise-generated data will be generated outside of centralized data centers by 2025. This volume of data places a tremendous strain on the internet, resulting in congestion and disruption. There are various advantages of this technology such as latency, performance, security and cost factor. One of the most effective ways to use edge computing is in smart home devices. A variety of IoT devices collect data from around the house in smart homes. The information is then transmitted to a remote server, where it is stored and processed. In the event of a network outage, this architecture may cause a number of issues. Edge computing can reduce backhaul costs and latency by bringing data storage and processing centers closer to the smart home.

However, I would like to conclude things have gotten even more efficient with edge computing. As a result, the quality of business operations has improved. Edge computing is a feasible solution for data-driven operations that require lightning-fast results and a high level of flexibility, depending on the current state of affairs.





Appears in
2023 - Spring - Issue 5