Abstract
Most previous research on job scheduling for multi-site distributed systems does not take into consideration behavioral trends when applying a scheduling method. In this paper, we address the scheduling of parallel jobs in a multi-site environment, where each site has a homogeneous cluster of non-dedicated processors where users submit jobs to be executed locally, while at the same time, external parallel jobs are submitted to a meta-scheduler. We use collected load data to model the performance trends that each site exhibits in order to predict load values via time-series analysis and then perform scheduling based on the predicted values.
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Ioannidou, M.A., Karatza, H.D. (2006). Multi-site Scheduling with Multiple Job Reservations and Forecasting Methods. In: Guo, M., Yang, L.T., Di Martino, B., Zima, H.P., Dongarra, J., Tang, F. (eds) Parallel and Distributed Processing and Applications. ISPA 2006. Lecture Notes in Computer Science, vol 4330. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11946441_80
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DOI: https://doi.org/10.1007/11946441_80
Publisher Name: Springer, Berlin, Heidelberg
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