Edge Computing refers to the process of transforming the manner in which data is handled, transformed and finally delivered, from a lot of devices across the world. The rapid development of internet-connected-devices or the IoT as well as the latest applications which require real-time computing power, proceeds in driving the edge-computing systems.
Gartner has defined edge computing as “a part of a distributed computing topology in which information processing is located close to the edge – where things and people produce or consume that information.”
At the elementary level, edge computing brings the computation and data storage proximate to the place where the devices are being assembled, rather than depending upon a dominant location which may be thousand miles away. This is being done with a view that data, more significantly real-time data does not face any latency issues that can hamper the performance of an application. Also, another advantage is that, the company can save on their cost by locally doing the processing, thus limiting the amount of data that requires to be processed in a cloud or centralized location.
The need of edge computing arose due to the rapid growth of the IoT devices that generates a huge amount of data during the course of operations. The following are the basic characteristics of edge computing: -
- Distributed geographically
- Interactions occur in real-time
- Heterogenous in nature
- Low latency and contextual
Faster network technologies like 5G wireless, allows for edge computing systems to boost up the development or support of the real-time applications, such as self-driving cars, video processing and analytics, robotics as well as artificial intelligence (AI).
The goals of edge computing in an earlier stage was to address the costs of bandwidth for data moving long distances due to the development of IoT-generated data, but the creation of real-time applications that requires transformation at the edge is supposed to drive this technology ahead.