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On advantages of scheduling using genetic fuzzy systems (2007)
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| Venue: | in Proceedings of the 12th Job Scheduling Strategies for Parallel Processing, ser. Lecture Notes in Computer Science (LNCS), E. Frachtenberg and |
| Citations: | 6 - 3 self |
BibTeX
@INPROCEEDINGS{Franke07onadvantages,
author = {Carsten Franke and Uwe Schwiegelshohn},
title = {On advantages of scheduling using genetic fuzzy systems},
booktitle = {in Proceedings of the 12th Job Scheduling Strategies for Parallel Processing, ser. Lecture Notes in Computer Science (LNCS), E. Frachtenberg and},
year = {2007},
pages = {68--93},
publisher = {Springer}
}
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Abstract
Abstract. In this paper, we present a methodology for automatically generating online scheduling strategies for a complex scheduling objective with the help of real life workload data. The scheduling problem includes independent parallel jobs and multiple identical machines. The objective is defined by the machine provider and considers different priorities of user groups. In order to allow a wide range of objective functions, we use a rule based scheduling strategy. There, a rule system classifies all possible scheduling states and assigns an appropriate scheduling strategy based on the actual state. The rule bases are developed with the help of a Genetic Fuzzy System that uses workload data obtained from real system installations. We evaluate our new scheduling strategies again on real workload data in comparison to a probability based scheduling strategy and the EASY standard scheduling algorithm. To this end, we select an exemplary objective function that prioritizes some user groups over others. 1
Keyphrases
genetic fuzzy system user group rule system possible scheduling state multiple identical machine wide range objective function real life workload data complex scheduling objective real system installation considers different priority online scheduling strategy machine provider appropriate scheduling strategy real workload data new scheduling strategy rule base scheduling problem exemplary objective function actual state easy standard independent parallel job
