PREDICTION OF DRMS WORKLOAD BY IDENTIFICATION OF PATTERNS IN JOB SUBMISSION PROCESSES
Andrey V. Gritsenko
Strony: 93-100
Opublikowano: 1 Jan 2012
Wyświetlenia: 261
Pobrania: 26
Streszczenie: Resource management and scheduling algorithms used in modern distributed resource management systems allow to utilize up to 80% of resources. In the course of studying the issue to augment this percentage a new approach, which consists in the application of prediction methods together with traditional for DRMS scheduling methods, was proposed. It is generally known that a fairly large part of all submitted jobs is formed by recurring job and using information about these jobs one can alter a job schedule for the purpose of increase of resource utilization. The process of simulation of a real sequence of submitted jobs with hidden cycles that inherently resemble white noise is described. On the basis of information about these cycles a prediction model is generated, which allow to simulate the process with enough high accuracy, and it in its turn confirms the assumption about potential appliance of forecasting methods in DRMS algorithms in order to raise their effectiveness.
Słowa kluczowe: distributed resource management systems, drms, job scheduling, forecasting methods
Cytowanie artykułu: Andrey V. Gritsenko. PREDICTION OF DRMS WORKLOAD BY IDENTIFICATION OF PATTERNS IN JOB SUBMISSION PROCESSES. Journal of International Scientific Publications: Materials, Methods & Technologies 6, 93-100 (2012). https://www.scientific-publications.net/en/article/1003157/
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