Energy-aware virtual machine consolidation for cloud data centers

Dabiah Ahmed M Al Alboaneen; Bernardi Pranggono; Huaglory Tianfield

doi:10.1109/UCC.2014.166

Energy-aware virtual machine consolidation for cloud data centers

Dabiah Ahmed M Al Alboaneen, Bernardi Pranggono, Huaglory Tianfield

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

31 Citations (Scopus)

Abstract

One of the issues in virtual machine consolidation (VMC) in cloud data centers is categorizing different workloads to classify the state of physical servers. In this paper, we propose a new scheme of host's load categorization in energy-performance VMC framework to reduce energy consumption while meeting the quality of service (QoS) requirement. Specifically the under loaded hosts are classified into three further states, i.e., Under loaded, normal and critical by applying the under load detection algorithm. We also design overload detection and virtual machine (VM) selection policies. The simulation results show that the proposed policies outperform the existing policies in Cloud Sim in terms of both energy and service level agreements violation (SLAV) reduction.

Original language	English
Title of host publication	Proceedings of the 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing
Publisher	IEEE
Pages	1010-1015
Number of pages	6
ISBN (Electronic)	9781479978816
ISBN (Print)	9781479978816
DOIs	https://doi.org/10.1109/UCC.2014.166
Publication status	Published - 2 Feb 2015
Event	7th IEEE/ACM international conference on Utility and Cloud Computing - London, United Kingdom Duration: 8 Dec 2014 → 11 Dec 2014

Conference

Conference	7th IEEE/ACM international conference on Utility and Cloud Computing
Abbreviated title	UCC'14
Country/Territory	United Kingdom
City	London
Period	8/12/14 → 11/12/14

Keywords

virtual machine consolidation (VMC)
energy-aware
energy-efficient
cloud data centres

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Documents and Links

10.1109/UCC.2014.166

Cite this

@inproceedings{39182db6a7c8467c968bd1eb088a6511,

title = "Energy-aware virtual machine consolidation for cloud data centers",

abstract = "One of the issues in virtual machine consolidation (VMC) in cloud data centers is categorizing different workloads to classify the state of physical servers. In this paper, we propose a new scheme of host's load categorization in energy-performance VMC framework to reduce energy consumption while meeting the quality of service (QoS) requirement. Specifically the under loaded hosts are classified into three further states, i.e., Under loaded, normal and critical by applying the under load detection algorithm. We also design overload detection and virtual machine (VM) selection policies. The simulation results show that the proposed policies outperform the existing policies in Cloud Sim in terms of both energy and service level agreements violation (SLAV) reduction.",

keywords = "virtual machine consolidation (VMC), energy-aware, energy-efficient, cloud data centres",

author = "Alboaneen, {Dabiah Ahmed M Al} and Bernardi Pranggono and Huaglory Tianfield",

year = "2015",

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day = "2",

doi = "10.1109/UCC.2014.166",

language = "English",

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booktitle = "Proceedings of the 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing",

publisher = "IEEE",

address = "United States",

note = "7th IEEE/ACM international conference on Utility and Cloud Computing , UCC'14 ; Conference date: 08-12-2014 Through 11-12-2014",

}

Alboaneen, DAMA, Pranggono, B & Tianfield, H 2015, Energy-aware virtual machine consolidation for cloud data centers. in Proceedings of the 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing. IEEE, pp. 1010-1015, 7th IEEE/ACM international conference on Utility and Cloud Computing , London, United Kingdom, 8/12/14. https://doi.org/10.1109/UCC.2014.166

TY - GEN

T1 - Energy-aware virtual machine consolidation for cloud data centers

AU - Alboaneen, Dabiah Ahmed M Al

AU - Pranggono, Bernardi

AU - Tianfield, Huaglory

PY - 2015/2/2

Y1 - 2015/2/2

N2 - One of the issues in virtual machine consolidation (VMC) in cloud data centers is categorizing different workloads to classify the state of physical servers. In this paper, we propose a new scheme of host's load categorization in energy-performance VMC framework to reduce energy consumption while meeting the quality of service (QoS) requirement. Specifically the under loaded hosts are classified into three further states, i.e., Under loaded, normal and critical by applying the under load detection algorithm. We also design overload detection and virtual machine (VM) selection policies. The simulation results show that the proposed policies outperform the existing policies in Cloud Sim in terms of both energy and service level agreements violation (SLAV) reduction.

AB - One of the issues in virtual machine consolidation (VMC) in cloud data centers is categorizing different workloads to classify the state of physical servers. In this paper, we propose a new scheme of host's load categorization in energy-performance VMC framework to reduce energy consumption while meeting the quality of service (QoS) requirement. Specifically the under loaded hosts are classified into three further states, i.e., Under loaded, normal and critical by applying the under load detection algorithm. We also design overload detection and virtual machine (VM) selection policies. The simulation results show that the proposed policies outperform the existing policies in Cloud Sim in terms of both energy and service level agreements violation (SLAV) reduction.

KW - virtual machine consolidation (VMC)

KW - energy-aware

KW - energy-efficient

KW - cloud data centres

U2 - 10.1109/UCC.2014.166

DO - 10.1109/UCC.2014.166

M3 - Conference contribution

SN - 9781479978816

SP - 1010

EP - 1015

BT - Proceedings of the 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing

PB - IEEE

T2 - 7th IEEE/ACM international conference on Utility and Cloud Computing

Y2 - 8 December 2014 through 11 December 2014

ER -

Energy-aware virtual machine consolidation for cloud data centers

Abstract

Conference

Keywords

UN SDGs

Documents and Links

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Cite this