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Authors: Soha Rawas ; Ahmed Zekri and Ali El Zaart

Affiliation: Beirut Arab University, Lebanon

Keyword(s): Carbon Footprint, Energy-efficient, Latency, Geo-distributed Data Centres.

Abstract: The proliferation of cloud computing due to its attracting on-demand services leads to the establishment of geo-distributed data centers (DCs) with thousands of computing and storage nodes. Consequently, many challenges exist for cloud providers to run such an environment. One important challenge is to minimize cloud users’ network latency while accessing services from the DCs. The other is to decrease the DCs’ energy consumption that contributes to high operational cost rates, low profits for cloud providers, and high carbon non-environment friendly emissions. In this paper, we studied the problem of virtual machine placement that results in less energy consumption, less CO2 emission, and less access latency towards largescale cloud providers operational cost minimization. The problem was formulated as multi-objective function and an intelligent machine-learning model constructed to improve the performance of the proposed model. To evaluate the proposed model, extensive sim ulation is conducted using the CloudSim simulator. The simulation results reveal the effectiveness of PCVM model compared to other competing virtual machine placement methods in terms of network latency, energy consumption, CO2 emission and operational cost minimization. (More)

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Paper citation in several formats:
Rawas, S.; Zekri, A. and El Zaart, A. (2018). Power and Cost-aware Virtual Machine Placement in Geo-distributed Data Centers. In Proceedings of the 8th International Conference on Cloud Computing and Services Science - CLOSER; ISBN 978-989-758-295-0; ISSN 2184-5042, SciTePress, pages 112-123. DOI: 10.5220/0006696201120123

@conference{closer18,
author={Soha Rawas. and Ahmed Zekri. and Ali {El Zaart}.},
title={Power and Cost-aware Virtual Machine Placement in Geo-distributed Data Centers},
booktitle={Proceedings of the 8th International Conference on Cloud Computing and Services Science - CLOSER},
year={2018},
pages={112-123},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006696201120123},
isbn={978-989-758-295-0},
issn={2184-5042},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Cloud Computing and Services Science - CLOSER
TI - Power and Cost-aware Virtual Machine Placement in Geo-distributed Data Centers
SN - 978-989-758-295-0
IS - 2184-5042
AU - Rawas, S.
AU - Zekri, A.
AU - El Zaart, A.
PY - 2018
SP - 112
EP - 123
DO - 10.5220/0006696201120123
PB - SciTePress