Problem statement: Meta-scheduling has become very important due to the increased number of submitted jobs for execution. Approach: We considered the job type in the scheduling decision that was not considered previously. Each job can be categorized into two types namely, dataintensive and computational-intensive in a specific ratio. Job ratio reflected the exact level of the job type in two specific numbers in the form of ratio and was computed to match the appropriate sites for the jobs in order to decrease the job turnaround time. Moreover, the number of jobs in the queue was considered in the batch decision to ensure server-load balancing. Results: The new factor that we considered namely, the job ratio can reduce the job turnaround time by submitting jobs in batches rather than submitting the jobs one by one. Conclusion: Our proposed system can be implemented in any middleware to provide job scheduling service.

Meta-scheduling systems play a crucial role in scheduling jobs that are submitted for execution and require special attention because an increasing number of jobs are being executed using a limited number of resources. The primary problem of meta-scheduling is selecting the best resources (sites) to use to execute the underlying jobs while still achieving the following objectives: reducing the mean job turnaround time, ensuring site load balance, and considering job priorities. We introduce an enhanced meta-scheduling system, called Job Nature Meta-scheduling over Grid (JNMgrid), that achieves these objectives. JNMgrid consists of three components: (1) Job Analyzer and Monitor, which is responsible for determining the types of jobs in specific ratios; (2) Job Decider, which is responsible for matching the jobs with the appropriate resources; and (3) Job Batcher, which is responsible for determining the best number of jobs for execution. The performance of JNMgrid is compared with similar existing systems, such as Random, Queue Length, File Access Cost, and File Access Cost + Job Queue Access Cost. The simulation results demonstrate that JNMgrid outperforms these systems and can thus be deployed in any grid middleware to improve sharing of limited resources among grid users.