TY - GEN
T1 - Intelligent OS process scheduling using fuzzy inference with user models
AU - Lim, Sungsoo
AU - Cho, Sung Bae
PY - 2007
Y1 - 2007
N2 - The process scheduling aims to arrange CPU time to multiple processes for providing users with more efficient throughput. Except the class of process set by user, conventional operating systems have applied the equivalent scheduling policy to every process. Moreover, if the scheduling policy is once determined, it is unable to change without resetting the operating system which takes much time. In this paper, we propose an intelligent CPU process scheduling algorithm using fuzzy inference with user models. It classifies processes into three classes, batch, interactive and real-time processes, and models user's preferences to each process class. Finally, it assigns the priority of each process according to the class of the process and user's preference through the fuzzy inference. The experimental result shows the proposed method can adapt to user and allow different scheduling policies to multiple users.
AB - The process scheduling aims to arrange CPU time to multiple processes for providing users with more efficient throughput. Except the class of process set by user, conventional operating systems have applied the equivalent scheduling policy to every process. Moreover, if the scheduling policy is once determined, it is unable to change without resetting the operating system which takes much time. In this paper, we propose an intelligent CPU process scheduling algorithm using fuzzy inference with user models. It classifies processes into three classes, batch, interactive and real-time processes, and models user's preferences to each process class. Finally, it assigns the priority of each process according to the class of the process and user's preference through the fuzzy inference. The experimental result shows the proposed method can adapt to user and allow different scheduling policies to multiple users.
UR - http://www.scopus.com/inward/record.url?scp=37249067001&partnerID=8YFLogxK
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U2 - 10.1007/978-3-540-73325-6_72
DO - 10.1007/978-3-540-73325-6_72
M3 - Conference contribution
AN - SCOPUS:37249067001
SN - 9783540733225
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 725
EP - 734
BT - New Trends in Applied Artificial Intelligence - 20th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, lEA/AlE 2007, Proceedings
PB - Springer Verlag
T2 - 20th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, lEA/AlE-2007
Y2 - 26 June 2007 through 29 June 2007
ER -