A Multi-criteria job scheduling framework for large computing farms (Contributo in atti di convegno)

Type

• Prodotto della ricerca (Classe)
• Contributo in atti di convegno (Classe)

Label

• A Multi-criteria job scheduling framework for large computing farms (Contributo in atti di convegno) (literal)

Anno

• 2010-01-01T00:00:00+01:00 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi

• 10.1109/CIT.2010.69 (literal)

Alternative label

• Baraglia R.; Dazzi P.; Capannini G.; Pagano G. (2010)
  A Multi-criteria job scheduling framework for large computing farms
  in 10th IEEE International Conference on Computer and Information Technology, Bradford, UK, 29 June - 1 July 2010
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Baraglia R.; Dazzi P.; Capannini G.; Pagano G. (literal)

Pagina inizio

• 187 (literal)

Pagina fine

• 194 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url

• http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5578454 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note

• In: CIT 2010 - 10th IEEE International Conference on Computer and Information Technology (Bradford, UK, 29 giugno - 1 luglio 2010). Proceedings, pp. 187 - 194. IEEE, 2010. (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#descrizioneSinteticaDelProdotto

• ABSTRACT: In this paper, we propose a multi-criteria job scheduler for scheduling a continuous stream of batch jobs on largescale computing farms, called Convergent Scheduling 2.0 (CS 2.0), which is an enhancement of the scheduler described in [5]. CS 2.0 exploits a set of heuristics that drive the scheduler in taking decisions. Each heuristics manages a specific constraint, and contributes to compute the measurement of the matching degree between a job and a machine. Scheduling choices are taken both to meet the QoS requested by the submitted jobs and to optimize the exploitation of hardware and software resources. In order to validate CS 2.0, we compared it versus two common job scheduling algorithms: Easy and Flexible backfilling. CS 2.0 demonstrated to be able to compute good assignments that allow a better exploitation of resources with respect to the other algorithms. (literal)

Note

• ISI Web of Science (WOS) (literal)
• PuMa (literal)
• Scopu (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• CNR-ISTI Dipartimento di Informatica, Università di Pisa (literal)

Titolo

• A Multi-criteria job scheduling framework for large computing farms (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn

• 978-1-4244-7547-6 (literal)

Abstract

• In this paper, we propose a multi-criteria job scheduler for scheduling a continuous stream of batch jobs on large-scale computing farms, called Convergent Scheduling 2.0 (CS 2.0), which is an enhancement of the scheduler described in [5]. CS 2.0 exploits a set of heuristics that drive the scheduler in taking decisions. Each heuristics manages a specific constraint, and contributes to compute the measurement of the matching degree between a job and a machine. Scheduling choices are taken both to meet the QoS requested by the submitted jobs and to optimize the exploitation of hardware and software resources. In order to validate CS 2.0, we compared it versus two common job scheduling algorithms: Easy and Flexible backfilling. CS 2.0 demonstrated to be able to compute good assignments that allow a better exploitation of resources with respect to the other algorithms. (literal)

Prodotto di

• Sistemi e algoritmi per Big Data (ICT.P09.006.001) (Modulo)
• Istituto di scienza e tecnologie dell'informazione \"Alessandro Faedo\" (ISTI) (Istituto)

Autore CNR

• Giancarlo Pagano (Persona)
• PATRIZIO DAZZI (Unità di personale interno)
• GABRIELE CAPANNINI (Unità di personale esterno)
• RANIERI BARAGLIA (Unità di personale interno)

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• Parole chiave di "A Multi-criteria job scheduling framework for large computing farms" (Insieme di parole chiave)

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Prodotto

• Istituto di scienza e tecnologie dell'informazione \"Alessandro Faedo\" (ISTI) (Istituto)
• Sistemi e algoritmi per Big Data (ICT.P09.006.001) (Modulo)

Autore CNR di

• RANIERI BARAGLIA (Unità di personale interno)
• GABRIELE CAPANNINI (Unità di personale esterno)
• Giancarlo Pagano (Persona)
• PATRIZIO DAZZI (Unità di personale interno)

Insieme di parole chiave di

• Parole chiave di "A Multi-criteria job scheduling framework for large computing farms" (Insieme di parole chiave)