On demand elastic capacity planning for service auto-scaling

Pavel Chuprikov; Sergey Nikolenko; Kirill Kogan

doi:10.1109/INFOCOM.2016.7524616

On demand elastic capacity planning for service auto-scaling

Pavel Chuprikov
, Sergey Nikolenko
, Kirill Kogan

Mathematical Institute
Institute IMDEA Networks
National Research University

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collection › Contribution à une conférence › Revue par des pairs

Résumé

Cloud computing allows on demand elastic service scaling. The capability of a service to predict resource requirements for the next operational period defines how well it will exploit the elasticity of cloud computing in order to reduce operational costs. In this work, we consider a capacity planning process for service scale-out as an online pricing model. In particular, we study the impact of buffering service requests on revenues in various settings with allocation and maintenance costs. In addition, we analyze the incurred latency implied by buffering service requests. We believe that our insights will allow to significantly simplify predictions and mitigate the unknowns of future demands on resources.

langue originale	Anglais
titre	IEEE INFOCOM 2016 - 35th Annual IEEE International Conference on Computer Communications
Editeur	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronique)	9781467399531
Les DOIs	https://doi.org/10.1109/INFOCOM.2016.7524616
état	Publié - 27 juil. 2016
Modification externe	Oui
Evénement	35th Annual IEEE International Conference on Computer Communications, IEEE INFOCOM 2016 - San Francisco, États-Unis Durée: 10 avr. 2016 → 14 avr. 2016

Série de publications

Nom	Proceedings - IEEE INFOCOM
Volume	2016-July
ISSN (imprimé)	0743-166X

Une conférence

Une conférence	35th Annual IEEE International Conference on Computer Communications, IEEE INFOCOM 2016
Pays/Territoire	États-Unis
La ville	San Francisco
période	10/04/16 → 14/04/16

Accès au document

10.1109/INFOCOM.2016.7524616

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Lien vers la publication dans Scopus

Contient cette citation

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title = "On demand elastic capacity planning for service auto-scaling",

abstract = "Cloud computing allows on demand elastic service scaling. The capability of a service to predict resource requirements for the next operational period defines how well it will exploit the elasticity of cloud computing in order to reduce operational costs. In this work, we consider a capacity planning process for service scale-out as an online pricing model. In particular, we study the impact of buffering service requests on revenues in various settings with allocation and maintenance costs. In addition, we analyze the incurred latency implied by buffering service requests. We believe that our insights will allow to significantly simplify predictions and mitigate the unknowns of future demands on resources.",

author = "Pavel Chuprikov and Sergey Nikolenko and Kirill Kogan",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 35th Annual IEEE International Conference on Computer Communications, IEEE INFOCOM 2016 ; Conference date: 10-04-2016 Through 14-04-2016",

year = "2016",

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Chuprikov, P, Nikolenko, S & Kogan, K 2016, On demand elastic capacity planning for service auto-scaling. Dans IEEE INFOCOM 2016 - 35th Annual IEEE International Conference on Computer Communications., 7524616, Proceedings - IEEE INFOCOM, VOL. 2016-July, Institute of Electrical and Electronics Engineers Inc., 35th Annual IEEE International Conference on Computer Communications, IEEE INFOCOM 2016, San Francisco, États-Unis, 10/04/16. https://doi.org/10.1109/INFOCOM.2016.7524616

On demand elastic capacity planning for service auto-scaling. / Chuprikov, Pavel; Nikolenko, Sergey; Kogan, Kirill.
IEEE INFOCOM 2016 - 35th Annual IEEE International Conference on Computer Communications. Institute of Electrical and Electronics Engineers Inc., 2016. 7524616 (Proceedings - IEEE INFOCOM; Vol 2016-July).

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collection › Contribution à une conférence › Revue par des pairs

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PY - 2016/7/27

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N2 - Cloud computing allows on demand elastic service scaling. The capability of a service to predict resource requirements for the next operational period defines how well it will exploit the elasticity of cloud computing in order to reduce operational costs. In this work, we consider a capacity planning process for service scale-out as an online pricing model. In particular, we study the impact of buffering service requests on revenues in various settings with allocation and maintenance costs. In addition, we analyze the incurred latency implied by buffering service requests. We believe that our insights will allow to significantly simplify predictions and mitigate the unknowns of future demands on resources.

AB - Cloud computing allows on demand elastic service scaling. The capability of a service to predict resource requirements for the next operational period defines how well it will exploit the elasticity of cloud computing in order to reduce operational costs. In this work, we consider a capacity planning process for service scale-out as an online pricing model. In particular, we study the impact of buffering service requests on revenues in various settings with allocation and maintenance costs. In addition, we analyze the incurred latency implied by buffering service requests. We believe that our insights will allow to significantly simplify predictions and mitigate the unknowns of future demands on resources.

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U2 - 10.1109/INFOCOM.2016.7524616

DO - 10.1109/INFOCOM.2016.7524616

M3 - Conference contribution

AN - SCOPUS:84983304261

T3 - Proceedings - IEEE INFOCOM

BT - IEEE INFOCOM 2016 - 35th Annual IEEE International Conference on Computer Communications

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 35th Annual IEEE International Conference on Computer Communications, IEEE INFOCOM 2016

Y2 - 10 April 2016 through 14 April 2016

ER -

On demand elastic capacity planning for service auto-scaling

Résumé

Série de publications

Une conférence

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