Grid computing involves the use of distributed computing resources in order to reach a common goal. Grid computing can be thought as a distributed system which includes non-interactive workload and a large number of files. There is a difference between the conventional high-performance computing system and grid computing, as in grid computers each node includes different applications and tasks. Grid computing tends to be more heterogeneous as well as geographically dispersed as compared to cluster computers. Grids are a form of distributed computing in which super virtual computer is included composed of mainy loosely coupled computers in order to perform a large number of tasks (Lathia, 2005).
Grid computing and its concepts
A grid is composed of a number of resources which are sometimes addressed by different names such as donors, host engines, nodes, members, and clients. In the computational grid system, resources are high performance servers. There are a number of components that are used in grid computing discussed as follow:
- Computation: on the grid system, the computing cycles are provided by the processes.
- Storage: the data storage is represented in the grid which refers to the primary storage and memory attached to the processor. Secondary storage refers to the hard disc drive. Data may also be stored on the storage devices that include several machines in a grid.
- Communications: this refers to the communication within the grid system and external grid system. It is essential to consider the communication within the grid system in order to properly access data which resides on multiple machines. Communication between grid which is specially and geographically distributed takes place through the internet (Gu & Grossman, 2003).
- Licenses and software: a grid computing system is able to provide the opportunity in order to install specific software only on a few If a job requires this software, the job can be sent to a machine in which a particular software is installed. By doing so the organization can save the significant expenses on the licensing fees (Bhutani, n.d.).
- Jobs and applications: in the grid computing application refers to the highest level of work and is broken down into a number of jobs. These jobs in the grid system and application are programmed in order to execute a parallel task on different machines.
- Scheduling and reservation: A grid system includes a job scheduler in order to schedule the jobs on the basis of appropriateness and availability of the resources.
Importance of grid computing
- In many of the organizations, there is a large amount of data which requires computational processing power. Along with this, there is also a huge amount of unused storage capacity which resides on the machines. Grid computing is able to provide a framework in order to exploit these underutilized resources. Another important grid computing contribution is that it enables as well as simplifies the collaboration among different organizations.
- This collaboration is not only concerned with the sharing of files and resources but is also able to directly access the services and other resources. Heterogeneous system distributed can also work together in order to create the image of the virtual computing system that offers a variety of virtual resources.
- With the use of grid, computing jobs can be parallelly executed which speeds up the overall performance.
- A number of policies of an organization can be easily managed with the use of grid software which is considered as the brain of the grid.
- Grid computing is able to resolve a number of complex and large problems in a short interval of time in which the existing hardware can be used properly in order to easily collaborate with other organization.
- There is no need to buy large SMP servers for the applications in order to split up as well as frame out the smaller commodity types of servers. Grid computing is important in order to provide efficient use of all the idle resources in which jobs can be framed out in efficient
- Bhutani, S. importance of Grid Computing and Its Concept. Journal Of Advances In Science And Technology, 3(3). Retrieved from http://www.ignited.in/a/1346
- Lathia, M. (2005). Advantages of Grid Computing. IEEE Distributed Systems Online, 6(2), 5-5. doi: 10.1109/mdso.2005.7
- Gu, Y., & Grossman, R. (2003). SABUL: A Transport Protocol for Grid Computing. Journal Of Grid Computing, 1(4), 377-386. doi: 10.1023/b:grid.0000037553.18581.3b