For years, cloud computing was synonymous with centralization. That era is over. Enter: the distributed cloud.

To understand the basic and complex differences between cloud and grid computing, we really need to explain both technologies. Here’s how they are defined. Cloud computing ...

Today we dive deeper into the differences between centralized and distributed performance optimization solutions. The technical functions that Centralized and Distributed ADS solutions perform are ...

Folks often get confused about the difference between centralized (a.k.a., asymmetrical or single ended) and distributed (a.k.a., symmetrical or dual-ended) application performance solutions.

A form of distributed computing, edge computing enables compute power to be closer to far-flung sources of data. Written by eWEEK content and product recommendations are editorially independent ...

The basics of distributed computing. Any time a workload is distributed between two or more computing devices or machines connected by some type of network, that’s distributed computing. There are a ...

In an edge-enabled computing environment, it’s not just a matter of what should be on the edge, but which edge it should be on and how the workloads get migrated between computing locations.

The rise of the Internet has pushed many applications from distributed to centralized. Back in the 1990s, we were all evolving from mainframes to local area networking and client/service development.

Prior to selecting the right motion control architecture for your application, be sure to understand the pros and cons of each method to determine which one best fits your needs.

Each of these levels has a solution that is a naturally better fit than the others. The key to unlocking the best-fitting IoT solution is understanding the differences between them.