TIME AND RESOURCE EFFICIENCY
The use of grid computing allows you to break down a huge, complex task into smaller, easy-to-execute tasks that run on different computers simultaneously. At the same time, the results of calculations are achieved in a shorter time and with efficient use of available resources.
COST SAVINGS
Grid computing allows you to reuse existing hardware resources to solve various tasks. This eliminates the need to purchase additional resources, as grid computing allows you to use resources in the cloud if the necessary equipment is located in other physical locations.
PHYSICAL FLEXIBILITY
Since grid computing networks are structured in different physical locations, this practice provides users with flexibility and allows them to collaborate and utilize hardware resources located in different geographical locations.
Limitations of grid computing
CONTINUOUS OPTIMIZATION
Grid middleware requires constant optimization. Since middleware is just like any other software, there is always a risk of bugs or something not working the way it should. In addition, since the type of middleware used depends on the capabilities of the management node, if we upgrade the hardware, the middleware must change accordingly.
HIGH SPEED REQUIREMENTS
To increase the efficiency of grid computers, systems need ultra-fast connections between different computer resources to utilize the full potential of the grid. Speed is one of the main reasons why we use grid computing, so slow connections between nodes hinder the use of grid computing.
SENSITIVITY OF THE CONTROL NODE
Problems in the control node can bring the entire network to a halt. If the middleware on the management node crashes or the management node loses power, the network will not be available until the management node is fully functional again.