Cloud data centers revenue maximization using server consolidation: Modeling and evaluation

Mohammad Wardat; Mahmoud Al-Ayyoub; Yaser Jararweh; Abdallah Khreishah

doi:10.1109/INFCOMW.2018.8406968

Cloud data centers revenue maximization using server consolidation: Modeling and evaluation

Mohammad Wardat, Mahmoud Al-Ayyoub, Yaser Jararweh, Abdallah Khreishah

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Scopus citations

Abstract

Cloud based data centers (DC) offering of virtually unlimited processing and storage capabilities faced a critical downside related to the enormous power consumption requirements. Powering and cooling DC has considerable share of the total DC operational costs in addition to the carbon tax. Server consolidation has been proposed as one viable solution that guarantees efficient power usage while maintaining quality of service requirements for the DC's services. This approach is simply about turning on and off the DC resources based on the incoming workload. In this paper, we are extending our previous work on expansion strategies for cloud services providers by considering the server consolidation technique in order to maximize the DC revenues while maintaining their service quality and reducing their carbon footprints.

Original language	English (US)
Title of host publication	INFOCOM 2018 - IEEE Conference on Computer Communications Workshops
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	172-177
Number of pages	6
ISBN (Electronic)	9781538659793
DOIs	https://doi.org/10.1109/INFCOMW.2018.8406968
State	Published - Jul 6 2018
Event	2018 IEEE Conference on Computer Communications Workshops, INFOCOM 2018 - Honolulu, United States Duration: Apr 15 2018 → Apr 19 2018

Other

Other	2018 IEEE Conference on Computer Communications Workshops, INFOCOM 2018
Country/Territory	United States
City	Honolulu
Period	4/15/18 → 4/19/18

All Science Journal Classification (ASJC) codes

Control and Optimization
Artificial Intelligence
Computer Networks and Communications

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10.1109/INFCOMW.2018.8406968

Cite this

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title = "Cloud data centers revenue maximization using server consolidation: Modeling and evaluation",

abstract = "Cloud based data centers (DC) offering of virtually unlimited processing and storage capabilities faced a critical downside related to the enormous power consumption requirements. Powering and cooling DC has considerable share of the total DC operational costs in addition to the carbon tax. Server consolidation has been proposed as one viable solution that guarantees efficient power usage while maintaining quality of service requirements for the DC's services. This approach is simply about turning on and off the DC resources based on the incoming workload. In this paper, we are extending our previous work on expansion strategies for cloud services providers by considering the server consolidation technique in order to maximize the DC revenues while maintaining their service quality and reducing their carbon footprints.",

author = "Mohammad Wardat and Mahmoud Al-Ayyoub and Yaser Jararweh and Abdallah Khreishah",

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booktitle = "INFOCOM 2018 - IEEE Conference on Computer Communications Workshops",

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Wardat, M, Al-Ayyoub, M, Jararweh, Y & Khreishah, A 2018, Cloud data centers revenue maximization using server consolidation: Modeling and evaluation. in INFOCOM 2018 - IEEE Conference on Computer Communications Workshops. Institute of Electrical and Electronics Engineers Inc., pp. 172-177, 2018 IEEE Conference on Computer Communications Workshops, INFOCOM 2018, Honolulu, United States, 4/15/18. https://doi.org/10.1109/INFCOMW.2018.8406968

Cloud data centers revenue maximization using server consolidation : Modeling and evaluation. / Wardat, Mohammad; Al-Ayyoub, Mahmoud; Jararweh, Yaser et al.

INFOCOM 2018 - IEEE Conference on Computer Communications Workshops. Institute of Electrical and Electronics Engineers Inc., 2018. p. 172-177.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Cloud data centers revenue maximization using server consolidation: Modeling and evaluation

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