A Metaheuristic for Optimizing the Performance and the Fairness
in Job Scheduling Systems

D 2015

A Metaheuristic for Optimizing the Performance and the Fairness in Job Scheduling Systems

KLUSÁČEK, Dalibor a Hana RUDOVÁ

Základní údaje

Originální název

A Metaheuristic for Optimizing the Performance and the Fairness in Job Scheduling Systems

Autoři

KLUSÁČEK, Dalibor (203 Česká republika, domácí) a Hana RUDOVÁ (203 Česká republika, garant, domácí)

Vydání

Germany, Artificial-Intelligence Applications in Information and Communication Technologies, od s. 3-29, 27 s. 2015

Nakladatel

Springer

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Německo

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

tištěná verze "print"

Odkazy

URL

Kód RIV

RIV/00216224:14330/15:00081127

Organizační jednotka

Fakulta informatiky

ISBN

978-3-319-19832-3

ISSN

DOI

http://dx.doi.org/10.1007/978-3-319-19833-0_1

UT WoS

000377199200002

Klíčová slova anglicky

Job scheduling; Metaheuristic; Optimization; Fairness

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 29. 4. 2016 00:12, RNDr. Pavel Šmerk, Ph.D.

Anotace

V originále

Many studies in the past two decades focused on the problem of efficient resource management and job scheduling in large computational systems such as HPC clusters and Grids. For this purpose, the application of Artificial Intelligence-based methods such as metaheuristics has been proposed in many works. This chapter provides an overview of such works that involve metaheuristics and discusses why mainstream resource management and scheduling systems are instead using only a limited set of rather simple scheduling policies. We identify several reasons that are causing this situation, e.g., a common use of overly simplified problem definitions with rather naive job and machine models or an application of unrealistic optimization criteria. In order to solve aforementioned issues, this chapter proposes new complex and well designed approaches that involve the use of metaheuristic which periodically optimizes job scheduling plan using several real life based optimization criteria. Importantly, approaches described in this chapter are successfully used in practice, i.e., within a production job scheduler which manages the computing infrastructure of the Czech Centre for Education, Research and Innovation in ICT (CERIT Scientific Cloud).

Návaznosti

GAP202/12/0306, projekt VaV

Název: Dyschnet - Dynamické plánování a rozvrhování výpočetních a síťových zdrojů (Akronym: Dyschnet)

Investor: Grantová agentura ČR, Dyschnet - Dynamické plánování a rozvrhování výpočetních a síťových zdrojů

Citovat

KLUSÁČEK, Dalibor a Hana RUDOVÁ. A Metaheuristic for Optimizing the Performance and the Fairness in Job Scheduling Systems. In Yacine Laalaoui, Nizar Bouguila. Artificial-Intelligence Applications in Information and Communication Technologies. Germany: Springer, 2015, s. 3-29. ISBN 978-3-319-19832-3. Dostupné z: https://dx.doi.org/10.1007/978-3-319-19833-0_1.

@inproceedings{1313998,
   author = {Klusáček, Dalibor and Rudová, Hana},
   address = {Germany},
   booktitle = {Artificial-Intelligence Applications in Information and Communication Technologies},
   doi = {http://dx.doi.org/10.1007/978-3-319-19833-0_1},
   editor = {Yacine Laalaoui, Nizar Bouguila},
   keywords = {Job scheduling; Metaheuristic; Optimization; Fairness},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Germany},
   isbn = {978-3-319-19832-3},
   pages = {3-29},
   publisher = {Springer},
   title = {A Metaheuristic for Optimizing the Performance and the Fairness in Job Scheduling Systems},
   url = {http://link.springer.com/chapter/10.1007%2F978-3-319-19833-0_1},
   year = {2015}
}

TY  - JOUR
ID  - 1313998
AU  - Klusáček, Dalibor - Rudová, Hana
PY  - 2015
TI  - A Metaheuristic for Optimizing the Performance and the Fairness in Job Scheduling Systems
PB  - Springer
CY  - Germany
SN  - 9783319198323
KW  - Job scheduling
KW  - Metaheuristic
KW  - Optimization
KW  - Fairness
UR  - http://link.springer.com/chapter/10.1007%2F978-3-319-19833-0_1
L2  - http://link.springer.com/chapter/10.1007%2F978-3-319-19833-0_1
N2  - Many studies in the past two decades focused on the problem of efficient resource management and job scheduling in large computational systems such as HPC clusters and Grids. For this purpose, the application of Artificial Intelligence-based methods such as metaheuristics has been proposed in many works. This chapter provides an overview of such works that involve metaheuristics and discusses why mainstream resource management and scheduling systems are instead using only a limited set of rather simple scheduling policies. We identify several reasons that are causing this situation, e.g., a common use of overly simplified problem definitions with rather naive job and machine models or an application of unrealistic optimization criteria. In order to solve aforementioned issues, this chapter proposes new complex and well designed approaches that involve the use of metaheuristic which periodically optimizes job scheduling plan using several real life based optimization criteria. Importantly, approaches described in this chapter are successfully used in practice, i.e., within a production job scheduler which manages the computing infrastructure of the Czech Centre for Education, Research and Innovation in ICT (CERIT Scientific Cloud).
ER  -

KLUSÁČEK, Dalibor a Hana RUDOVÁ. A Metaheuristic for Optimizing the Performance and the Fairness in Job Scheduling Systems. In Yacine Laalaoui, Nizar Bouguila. \textit{Artificial-Intelligence Applications in Information and Communication Technologies}. Germany: Springer, 2015, s.~3-29. ISBN~978-3-319-19832-3. Dostupné z: https://dx.doi.org/10.1007/978-3-319-19833-0\_{}1.

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