An energy efficient VM allocation approach for data centers

Iksen Caglar; Deniz Turgay Altilar

doi:10.1109/BigDataSecurity-HPSC-IDS.2016.62

An energy efficient VM allocation approach for data centers

Iksen Caglar
, Deniz Turgay Altilar

Bilgisayar Mühendisliği Bölümü

Istanbul Technical University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

3 Atıf (Scopus)

Özet

Due to the rapid growth in the data storage and data processing demands, the energy consumption of data centers is becoming a key challenge. Live migration of Virtual Machine (VM) is commonly proposed to reduce energy consumption and to optimize resource usage in the literature although itcomes withessential drawbacks such as migration cost and Service Level Agreement Violation (SLAV). Anovel efficient resource management policy for virtualized data centers which optimizes the number of resources to meet requirements of dynamic workloads without migration is proposed in this paper. The proposed approach contains an experiment based prediction module. Energy-performance trade off relies on comparison of the predicted and the active number of servers periodically. The performance evaluations of the proposed approach are performed by using real-world workload traces from Planet Lab. The proposed algorithm is also compared to the other techniques proposed in the literature based on VM migration.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Proceedings - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016
Editörler	Meikang Qiu
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
Sayfalar	240-244
Sayfa sayısı	5
ISBN (Elektronik)	9781509024025
DOI'lar	https://doi.org/10.1109/BigDataSecurity-HPSC-IDS.2016.62
Yayın durumu	Yayınlandı - 30 Haz 2016
Etkinlik	2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016 - New York, United States Süre: 9 Nis 2016 → 10 Nis 2016

Yayın serisi

Adı	Proceedings - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016

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???event.eventtypes.event.conference???	2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016
Ülke/Bölge	United States
Şehir	New York
Periyot	9/04/16 → 10/04/16

Bibliyografik not

Publisher Copyright:
© 2016 IEEE.

BM SKH

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Belgeye Erişim

10.1109/BigDataSecurity-HPSC-IDS.2016.62

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Caglar, I., & Altilar, D. T. (2016). An energy efficient VM allocation approach for data centers. In M. Qiu (Ed.), Proceedings - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016 (pp. 240-244). Makale 7502296 (Proceedings - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigDataSecurity-HPSC-IDS.2016.62

Caglar, Iksen ; Altilar, Deniz Turgay. / An energy efficient VM allocation approach for data centers. Proceedings - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016. editör / Meikang Qiu. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 240-244 (Proceedings - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016).

@inproceedings{296e830c3ec242b48a1e0a3af78ba54e,

title = "An energy efficient VM allocation approach for data centers",

abstract = "Due to the rapid growth in the data storage and data processing demands, the energy consumption of data centers is becoming a key challenge. Live migration of Virtual Machine (VM) is commonly proposed to reduce energy consumption and to optimize resource usage in the literature although itcomes withessential drawbacks such as migration cost and Service Level Agreement Violation (SLAV). Anovel efficient resource management policy for virtualized data centers which optimizes the number of resources to meet requirements of dynamic workloads without migration is proposed in this paper. The proposed approach contains an experiment based prediction module. Energy-performance trade off relies on comparison of the predicted and the active number of servers periodically. The performance evaluations of the proposed approach are performed by using real-world workload traces from Planet Lab. The proposed algorithm is also compared to the other techniques proposed in the literature based on VM migration.",

keywords = "Cloud Computing, Energy Efficiency, Green Computing, Resource Management, VM Migration",

author = "Iksen Caglar and Altilar, \{Deniz Turgay\}",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016 ; Conference date: 09-04-2016 Through 10-04-2016",

year = "2016",

month = jun,

day = "30",

doi = "10.1109/BigDataSecurity-HPSC-IDS.2016.62",

language = "English",

series = "Proceedings - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "240--244",

editor = "Meikang Qiu",

booktitle = "Proceedings - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016",

address = "United States",

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Caglar, I & Altilar, DT 2016, An energy efficient VM allocation approach for data centers. in M Qiu (ed.), Proceedings - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016., 7502296, Proceedings - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016, Institute of Electrical and Electronics Engineers Inc., pp. 240-244, 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016, New York, United States, 9/04/16. https://doi.org/10.1109/BigDataSecurity-HPSC-IDS.2016.62

An energy efficient VM allocation approach for data centers. / Caglar, Iksen; Altilar, Deniz Turgay.
Proceedings - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016. ed. / Meikang Qiu. Institute of Electrical and Electronics Engineers Inc., 2016. p. 240-244 7502296 (Proceedings - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - An energy efficient VM allocation approach for data centers

AU - Caglar, Iksen

AU - Altilar, Deniz Turgay

PY - 2016/6/30

Y1 - 2016/6/30

N2 - Due to the rapid growth in the data storage and data processing demands, the energy consumption of data centers is becoming a key challenge. Live migration of Virtual Machine (VM) is commonly proposed to reduce energy consumption and to optimize resource usage in the literature although itcomes withessential drawbacks such as migration cost and Service Level Agreement Violation (SLAV). Anovel efficient resource management policy for virtualized data centers which optimizes the number of resources to meet requirements of dynamic workloads without migration is proposed in this paper. The proposed approach contains an experiment based prediction module. Energy-performance trade off relies on comparison of the predicted and the active number of servers periodically. The performance evaluations of the proposed approach are performed by using real-world workload traces from Planet Lab. The proposed algorithm is also compared to the other techniques proposed in the literature based on VM migration.

AB - Due to the rapid growth in the data storage and data processing demands, the energy consumption of data centers is becoming a key challenge. Live migration of Virtual Machine (VM) is commonly proposed to reduce energy consumption and to optimize resource usage in the literature although itcomes withessential drawbacks such as migration cost and Service Level Agreement Violation (SLAV). Anovel efficient resource management policy for virtualized data centers which optimizes the number of resources to meet requirements of dynamic workloads without migration is proposed in this paper. The proposed approach contains an experiment based prediction module. Energy-performance trade off relies on comparison of the predicted and the active number of servers periodically. The performance evaluations of the proposed approach are performed by using real-world workload traces from Planet Lab. The proposed algorithm is also compared to the other techniques proposed in the literature based on VM migration.

KW - Cloud Computing

KW - Energy Efficiency

KW - Green Computing

KW - Resource Management

KW - VM Migration

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U2 - 10.1109/BigDataSecurity-HPSC-IDS.2016.62

DO - 10.1109/BigDataSecurity-HPSC-IDS.2016.62

M3 - Conference contribution

AN - SCOPUS:84979780469

T3 - Proceedings - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016

SP - 240

EP - 244

BT - Proceedings - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016

A2 - Qiu, Meikang

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016

Y2 - 9 April 2016 through 10 April 2016

ER -

Caglar I, Altilar DT. An energy efficient VM allocation approach for data centers. In Qiu M, editör, Proceedings - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 240-244. 7502296. (Proceedings - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016). doi: 10.1109/BigDataSecurity-HPSC-IDS.2016.62

An energy efficient VM allocation approach for data centers

Özet

Yayın serisi

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Bibliyografik not

BM SKH

Belgeye Erişim

Diğer Dosyalar ve Linkler

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