Job Scheduling on Grid Computing Using First Fit, Best Fit, and Worst Fit

Grid computing can be considered large-scale distributed cluster computing and parallel distributed network processing. The two most important issues in managing user work are resource allocation and scheduling of required resources. When user jobs are submitted, they are managed by resource intermediaries who find and allocate the right resources. After the resource allocation stage, work scheduled on the existing resources according to the user's required resources. In most grid systems with traditional scheduling, jobs are submitted and placed in waiting room queues to wait for the required resources to become available. Each grid system can use a different scheduling algorithm to execute jobs based on other parameters, such as resources, delivery time, and execution duration. There is no guarantee that these traditional scheduling algorithms will get the job done. The First Come First Serve Left Right Hole Scheduling (FCFS-LRH) reservation strategy improves resource utilization in a grid system by using a local scheduler. Compared to traditional strategies. There are two objectives of this research. First, compare the first fit, best fit, and worst fit algorithms to find empty timeslots and place them in a virtual view. Second, reduce the idle time value. The results showed that the FCFS-LRH method could reduce the idle time value of the FCFS-EDF and FCFS methods. The overall execution time of the first fit with the FCFS-LRH strategy is better than the FCFS-EDF