The first and foremost is availability of matching resources. Another important parameter is proximity to the data, if distributed data processing is involved. However, since it is difficult to have up-to-date information and uniform priorities in Grid, the latest approach is to schedule generic tasks that pull payloads from a central queue after analyzing the environment in which they ended up.
the Grid environment is changing dynamically in time mainly due to load of the system, available network bandwidth and also due to other events such as resource or network failure or recovery.
thank u sir...but sir can u please elaborate me job failure rate in which sense. Plz also forward me the link of the research paper carried on the same topics in grid environment
On of the challenges of grid computing is to execute jobs on heterogeneous machines without much control over the machines availability. (machines can be removed from the grid at any point of time without warning).
Thus, the key parameter would be ensuring good performance on heterogeneous environment and jobs continuity in the event of machines failures.
you can use parameters like throughput , Reliability ,Durability ,Agility , Security . you can add parameters according to your needs and challenges for your Research Work .
Grid environment is heterogeneous in nature and it is dynamic (resource can join or leave at any time). In scheduling you have to consider this and you can use parameters like makespan, reliability, failures ....
Grid computing system is a widely distributed resource for a common goal. It is Brother of Cloud Computing and Sister of Supercomputer. We can think the grid is a distributed system connected to a single network. This types of computing work with the large volume of files. Basically, it is a cluster types system. So people call it cluster computing.
Grid computer tends to be more geographically disperse and heterogeneous by nature. Grid network also has various types. A single grid is like dedicated connection but a common grid perform multiple tasks.
The size of the grid is large. So grid computing is like supercomputing. It consists of many network, computer, and middleware. Grid computer is dedicated to some specific function of the large volume of data. In the grid process, each task divided into a various process. All the process starts execution simultaneously on a different computer. As a result, very few seconds needs to execute and enjoy the flavor of supercomputing.