What is Grid Computing?
Obtaining a common goal by the usage of distributed computers is termed as Grid Computing. Its maximum efficiency differentiates it from every other technology. Because, here, every different node is assigned to a different task, and they work as a cluster towards a single goal or outcome. Since they are separated physically and geographically, they behave heterogenous. An individual grid is assigned to execute a common application, and together it is applied for different purposes. The grid is a large system that is built with middleware software libraries. The working and components of the grid system and its important features are explained in this article.
How does Grid Computing Works?
The advancement of the grid computing system is increasing day-by-day. There are many other kinds of research and advanced developments happening in grid computing, supporting the implementation of new standards and protocols. But the working of the standard grid computing system is as follows,
CPU, Memory and storage units are the fundamental units of the grid computing system. Based on the requirement and need, there might be a computer of one CPU or multiple CPUs. They have a microprocessor by which they perform all the mathematical functions. Finally, the processed information is sent to different memory locations. The memory of the computer is similar to the temporary electronic storage, which keeps the related data available for the microprocessor. The microprocessor has to search and extract the data from permanent storage components such as any hard disk or USB drives or reliable databases without any memory component. Storage is an important function in grid computing that should be open-source and accessible at any time.
With its own resources, the computer can work with certain limitations only. With the ability to add maximum power or capacity on a single computer, grid computing enables up-gradation and also performance increase. Storage of large data is made possible by the elasticity and the fast operation. The power of all the computers are cumulated, and it increases the power of the system. Also, the resources are connected together and let anyone access the computer. Considering this, from that individual user’s standpoint, his computer has switched into a supercomputer with high values of performance and operating speeds.
Components of Grid Computing
The components of grid computing are user interface, security, scheduler, data management, workload management and resource management.
As computers are arranged in a grid with multiple applications, it finds it difficult to manage any sensitive or valuable data. So the security of the grid system plays a major role, and it is implemented with some advanced techniques of authorization, encryption and decryption. It is challenging to access or retrieve any information on the grid system and so the user interface is implemented in a simplified version.
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Such as the interface offered by an application when the user is executing or the grid admin interface, much similar to a web portal that gives access to applications and available resources on the grid system. The most significant part is the interface made with the portal style, as it plays a major role in helping the user to teach how to query and execute various functions on the grid. Compact workload management can only be achieved when the application that the user requires to execute on the grid is aware of the available resources.
Now, the application interacts with the workload manager to find the available resource and update the status accordingly. A scheduler is required to position the computers on where the application is available and assigned with required jobs. Job queue priority helps in considering the alternative available resources and makes it a simple task. The scheduler has other important tasks, including maintaining the workload, finding uncompleted tasks, unveiling the resources reserved, and monitoring the entire system.
Suppose the application is executed on a system that doesn’t store the application needs and manage it as a secure network. So the consistent data management services take in charge of moving the data to suitable places across different machines managing various protocols. Handling the critical tasks such as scheduling the jobs with explicit resources and monitoring the jobs’ status, and extracting the results is perfectly accomplished by resource management. It potentially includes the operating grid system’s entire protocol and unleashes its scope to different applications, making it more reliable and successful.
Use Cases of grid Computing
The concept of grid computing is explored end to end from academics to research communities. The scope and deployment of grid computing became essential and mandatory in the market as similar to the internet. But the business has begun to stick on to the advantages of grid computing by enabling new types of business and financial models.
In the industry and financial services, grid computing can be implemented to speed up the transaction of trade and shrunk any high volume of data. In the field of IT, Grid computing enables the possibility to carry over any critical missions and circumstances that might not permit any downtime at all. The government agencies use grid computing to secure, segregate and pool up the higher dimensional stockpiles of information.
An organization like military and civilian agencies might require data integrity capabilities and a faster rate of information access involving collaboration with millions of cross-agent data repositories. There are many organizations involved in analyzing, such as genome resources and development in the pharmaceutical field, which relies on grid computing to clean, process, compare and cross-tabulate the enormous amount of data. The faster processing of data is a remarking edge in the deciding factor.
Conclusion
Biometric verification systems and biometric information security areas also make use of Grid computing as a large-scale enterprise. The BIS is considered a central workflow engine that became the mandatory process rather than traditional grid systems.
A genuine test case that is shown on computing the integration and workflow of the systems by the possession of an advanced grid middleware system makes it different. It represents multitasking activities and schedules the task in parallel to finish it effectively.
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