The Edge Computing Paradigm

Advantages, Challenges, and Applications in the IoT

- By Pedro Bertoleti

In the pre-Internet Dark Ages, all computing was done locally. Then storage and processing moved to the Cloud. Now, local models are gaining traction again. In this article, Pedro explores the fundamentals of edge computing. He explains the edge computing paradigm, compares it to the cloud-centric paradigm, then presents the advantages and challenges of edge computing, and some solutions in the IoT that could benefit from edge computing adoption.

The digital landscape is rapidly evolving, driven by the proliferation of Internet of Things (IoT) devices and the ever-increasing demand for real-time data processing. Traditional cloud computing models, while powerful, often struggle to keep pace with the latency and bandwidth requirements of these emerging applications. Also, from a perspective of cost savings, cloud computing models can be a bad choice—as solutions become more scalable, costs scale as well. The same is true for connectivity—as more data is transferred, the higher costs become.

This is where edge computing steps in, offering a distributed computing paradigm that brings computation and data storage closer to the source of data generation. By processing data at the “edge” of the network—near the devices and sensors that create it—edge computing unlocks a new realm of possibilities for efficiency, responsiveness, and autonomy. These include saving costs from cloud computing usage and connectivity, since only short amounts of data need to be transferred from end devices to the Cloud, processed, and stored in cloud-side.

This article explores the core concepts of edge computing, its advantages and challenges, the typical layers within edge computing architecture, and various solutions that stand to benefit significantly from its adoption. Understanding these fundamentals is crucial for anyone looking to leverage the power of edge computing in today’s connected world.

WHAT IS EDGE COMPUTING?