Edge Computing Evolution And Why It Is Important

The world is hyper-connected, and the need to find a way to scale and process data is increasing. There is a massive transformation in how data is processed, stored, and analyzed.

Moreover, there is a noticeable change in the goal of what edge computing is designed to achieve. Initially, it aims to lower the cost of bandwidth movement of data from the source to another location in the cloud.

The explosion of real-time applications indicates that little latency is required to transmit data to an entity. The recent surge in autonomous vehicles and multi-camera video protocols further pushes the edge computing concept.

In addition, 5G wireless technology is gaining traction, and the global drive for its adoption is rapidly growing. Interestingly, edge computing will immensely benefit from the 5G network due to the latter’s fast processing time and low-latency use case.

Introducing Edge Computing

By its simple definition, edge computing links computational and data storage closer to a device. It is the decentralization of applications working closely with several devices rather than one single device.

This is done to prevent real-time data latency and other issues affecting an application’s performance across several devices. Edge computing saves costs as it allows the company to process data locally instead of spending on cloud services.

Furthermore, edge computing hardware removes the bandwidth costs of transmitting and storing large amounts of data. Due to its real-time use, it is the most cost-efficient and reliable data storage and processing platform for the Internet of Things (IoT) users.

The Workings of Edge Computing

The physical structure of the system is a complex one. However, the basic understanding indicates that several users’ devices can connect to an edge platform for fast processing and responsive navigation.

IoT Edge devices include IoT sensors, several client gadgets and devices, smartphones, security cameras, and other internet-connected devices.

Although there is a difference between the individual use case of edge and the industrial use case, the individual user is the most basic and does not require much technical know-how to operate and use.

While in the industrial setting, the edge computing device is mostly an autonomous robot situated in a specific location within the premise. Depending on the industry, several edge devices can be adopted and used.

In other words, edge devices vary from one sector to another. In the health field, for example, it is mostly a high-level surgical system to help doctors perform surgery from remote positions.

However, terminology differs; in some settings, they are called edge gateways, while in others, they are known as edge servers. Service providers deploy the edge gateways depending on the services they render.

And the 5G network is increasingly becoming an integral part of edge computing for its vast processing ability. As 5G gets increasingly involved in edge computing, the relationship between the two will increase.

Edge Computing has many benefits as it can be integrated with many functionalities like Artificial intelligence (AI).