Essentially, Grid computing is an infrastructure that offers high-speed computing capacity in a distributed system by utilizing geographically distributed resources. Grid resources are owned by different organizations and have their own policies and access models. Scheduling future jobs in a grid system requires a data structure capable of handling parallel jobs, known as the Message Passing Interface (MPI). A data structure model needs to be proposed to minimize search time, and efficiently add and remove MPI jobs. Data structures that support future scheduling models will improve resource utilization efficiency. This research proposes a data structure capable of handling future MPI job scheduling to increase resource utilization. Experimental results on the data structure show that the average memory consumption of the FCFS-LRH data structure is lower than that of FCFS and FCFS-EDS. For average empty timeslot searches, FCFS-LRH is faster than FCFS-EDS but slower than FCFS. The average data insertion speed of FCFS-LRH is faster than that of FCFS-EDS.
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