A Machine Learning-Based Approach to Estimate the CPU-Burst Time for Processes in the Computational Grids

The implementation of CPU-Scheduling algorithms such as Shortest-Job-First (SJF) and Shortest Remaining Time First (SRTF) is relying on knowing the length of the CPU-bursts for processes in the ready queue. There are several methods to predict the length of the CPU-bursts, such as exponential averag...

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Veröffentlicht in:	2015 3rd International Conference on Artificial Intelligence, Modelling and Simulation (AIMS) S. 3 - 8
Hauptverfasser:	Helmy, Tarek, Al-Azani, Sadam, Bin-Obaidellah, Omar
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.12.2015
Schlagworte:	Artificial intelligence Computational modeling CPU Scheduling Algorithm CPU-Burst Feature Selection Machine Learning Scheduling algorithms Single machine scheduling Testing
Online-Zugang:	Volltext
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