u 2004

Uniform Job Scheduling Model for Distributed Processing Environment with Distributed Storage

HEJTMÁNEK, Lukáš a Petr HOLUB

Základní údaje

Originální název

Uniform Job Scheduling Model for Distributed Processing Environment with Distributed Storage

Název anglicky

Uniform Job Scheduling Model for Distributed Processing Environment with Distributed Storage

Vydání

13 s. Technical report 9/2004, 2004

Nakladatel

CESNET z.s.p.o.

Další údaje

Typ výsledku

Účelové publikace

Utajení

není předmětem státního či obchodního tajemství

Odkazy

Organizační jednotka

Ústav výpočetní techniky

Klíčová slova anglicky

scheduling; uniform tasks; PO-class scheduling algorithm; network traffic prediction service;
Změněno: 29. 8. 2013 14:50, doc. RNDr. Petr Holub, Ph.D.

Anotace

V originále

In this report, we describe components, algorithms and mathematical details for the scheduling jobs with respect to distributed both computing capacity and storage capacity. The work was designed for distributed video processing in Grid environments described in [5]. The video processing features important advantage of having almost exactly uniform job size and thus the scheduling algorithm may belong to PO class under certain assumptions discussed here. Furthermore we provide in-depth discussion of requirements on network traficc prediction services that need to be used to optimize data location with respect to available processing capacity and vice versa.

Anglicky

In this report, we describe components, algorithms and mathematical details for the scheduling jobs with respect to distributed both computing capacity and storage capacity. The work was designed for distributed video processing in Grid environments described in [5]. The video processing features important advantage of having almost exactly uniform job size and thus the scheduling algorithm may belong to PO class under certain assumptions discussed here. Furthermore we provide in-depth discussion of requirements on network traficc prediction services that need to be used to optimize data location with respect to available processing capacity and vice versa.