As compared with supercomputers and PCs, the higher rate of unsuccessful job execution in today's distributed and large systems like clusters and grids is a significant reason behind squandering of their resources. Although many approaches have been proposed in order to make these environments more fault tolerant, their great overhead convinces the researchers to look for preventive methods. In this work, we employ a job futurity predictor to manage the arriving jobs efficiently. To this end, a novel meta–scheduler sub–component called Job Submission Manager (JSM) is proposed. The main role of JSM is to filter the incoming jobs according to some parameters such as current system load, job failure probability. The experimental results based on two different modelling approaches indicate that this managing component can effectively influence the system throughput and increase the utilisation of computing resources.

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