Scheduling Scientific Workloads in Private Cloud: Problems and
Approaches

D 2017

Scheduling Scientific Workloads in Private Cloud: Problems and Approaches

KLUSÁČEK, Dalibor, Boris PARÁK, Gabriela PODOLNÍKOVÁ and András ÜRGE

Basic information

Original name

Scheduling Scientific Workloads in Private Cloud: Problems and Approaches

Authors

KLUSÁČEK, Dalibor (203 Czech Republic), Boris PARÁK (703 Slovakia), Gabriela PODOLNÍKOVÁ (203 Czech Republic, guarantor, belonging to the institution) and András ÜRGE (703 Slovakia, belonging to the institution)

Edition

New York, 10th International Conference on Utility and Cloud Computing (UCC 2017), p. 9-18, 10 pp. 2017

Publisher

ACM

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

RIV identification code

RIV/00216224:14330/17:00118585

Organization unit

Faculty of Informatics

ISBN

978-1-4503-5149-2

DOI

http://dx.doi.org/10.1145/3147213.3147223

UT WoS

000568256400005

Keywords in English

Private Cloud; Fairness; Fair-Sharing; Scheduling; OpenNebula

Abstract

V originále

Public cloud providers are using the "pay-per-use" model when providing their resources to customers. Among other advantages, it allows the provider to react to changing demands, e.g., by modifying prices or by extending its physical capacities using the profit obtained. In this paper we deal with a completely different model. We describe a private scientific cloud where resources are provided to researchers for free. As we demonstrate, the "absence of money" means that the system must employ other mechanisms to guarantee reasonable performance and utilization. Especially, the problem of guaranteeing user-to-user fairness represents a major issue. Moreover, since there is no financial burden related to the use of cloud infrastructure, many resources can be wasted by long running idle virtual machines (VM) that their users no longer need. This leads to underutilization and resource fragmentation. This paper discusses these problems using real-life data from the CERIT Scientific Cloud and proposes several techniques to guarantee fair and efficient use of system resources. Furthermore, we present a prototype of a new experimental OpenNebula-compatible VM scheduler which was designed as a replacement for the default scheduler provided in OpenNebula distribution. Unlike the default scheduler, our new scheduler provides complex fair-sharing mechanisms as well as modular and easy-to-extend architecture to enable further development of advanced VM scheduling policies.

Citovat

KLUSÁČEK, Dalibor, Boris PARÁK, Gabriela PODOLNÍKOVÁ and András ÜRGE. Scheduling Scientific Workloads in Private Cloud: Problems and Approaches. Online. In 10th International Conference on Utility and Cloud Computing (UCC 2017). New York: ACM, 2017, p. 9-18. ISBN 978-1-4503-5149-2. Available from: https://dx.doi.org/10.1145/3147213.3147223.

@inproceedings{1768262,
   author = {Klusáček, Dalibor and Parák, Boris and Podolníková, Gabriela and Ürge, András},
   address = {New York},
   booktitle = {10th International Conference on Utility and Cloud Computing (UCC 2017)},
   doi = {http://dx.doi.org/10.1145/3147213.3147223},
   keywords = {Private Cloud; Fairness; Fair-Sharing; Scheduling; OpenNebula},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {New York},
   isbn = {978-1-4503-5149-2},
   pages = {9-18},
   publisher = {ACM},
   title = {Scheduling Scientific Workloads in Private Cloud: Problems and Approaches},
   year = {2017}
}

TY  - JOUR
ID  - 1768262
AU  - Klusáček, Dalibor - Parák, Boris - Podolníková, Gabriela - Ürge, András
PY  - 2017
TI  - Scheduling Scientific Workloads in Private Cloud: Problems and Approaches
PB  - ACM
CY  - New York
SN  - 9781450351492
KW  - Private Cloud
KW  - Fairness
KW  - Fair-Sharing
KW  - Scheduling
KW  - OpenNebula
N2  - Public cloud providers are using the "pay-per-use" model when providing their resources to customers. Among other advantages, it allows the provider to react to changing demands, e.g., by modifying prices or by extending its physical capacities using the profit obtained. In this paper we deal with a completely different model. We describe a private scientific cloud where resources are provided to researchers for free. As we demonstrate, the "absence of money" means that the system must employ other mechanisms to guarantee reasonable performance and utilization. Especially, the problem of guaranteeing user-to-user fairness represents a major issue. Moreover, since there is no financial burden related to the use of cloud infrastructure, many resources can be wasted by long running idle virtual machines (VM) that their users no longer need. This leads to underutilization and resource fragmentation. This paper discusses these problems using real-life data from the CERIT Scientific Cloud and proposes several techniques to guarantee fair and efficient use of system resources. Furthermore, we present a prototype of a new experimental OpenNebula-compatible VM scheduler which was designed as a replacement for the default scheduler provided in OpenNebula distribution. Unlike the default scheduler, our new scheduler provides complex fair-sharing mechanisms as well as modular and easy-to-extend architecture to enable further development of advanced VM scheduling policies.
ER  -

KLUSÁČEK, Dalibor, Boris PARÁK, Gabriela PODOLNÍKOVÁ and András ÜRGE. Scheduling Scientific Workloads in Private Cloud: Problems and Approaches. Online. In \textit{10th International Conference on Utility and Cloud Computing (UCC 2017)}. New York: ACM, 2017, p.~9-18. ISBN~978-1-4503-5149-2. Available from: https://dx.doi.org/10.1145/3147213.3147223.

Detailed Information on Publication Record