When grid computing was first introduced, it was based on the idea that computing power, like electricity, could be consumed from a network. Today, this idea is reflected in the concept of cloud computing, while grid computing is better defined as a distributed network of shared computer systems.
Applications of grid computing include big data analysis and resource-intensive modeling. Grid systems are highly effective in performing tasks that require high computing power, as all connected computers combine their computing power, storage, and other capabilities together through a network. Some experts classify grid computing as a subcategory of distributed computing.
A grid computer works like a virtual supercomputer made up of machines connected to a network such as Ethernet or the Internet. Grid computing can also be categorized as parallel computing, where multiple CPU cores are scattered in many locations instead of running on a single machine.
Although the concept of grid computing has been around for more than two decades, different organizations and industries follow different protocols – no standard rules for grid computing have been established or accepted worldwide. A grid computing system can consist of many computers with the same configuration (a homogeneous network) or several different types of computers with different configurations (a heterogeneous network).