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Cited by 12Cloud Computing and Resource ManagementEnergy Efficiency in ComputingDistributed and Parallel Computing Systems

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LECC: Location, energy, carbon and cost-aware VM placement model in geo-distributed DCs

Rawas, Soha, Zekri, Ahmed, El-Zaart, Ali·2022·Sustainable Computing: Informatics and Systems
DOI 10.1016/j.suscom.2021.100649
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Research works printed but not linked: 23

  1. Rawas, 2021, EEBA: energy-efficient and bandwidth-aware workload allocation method for data-intensive applications in cloud data centers, IAENG Int. J. Comput. Sci., 48
  2. Rawas, 2021, Energy, network, and application-aware virtual machine placement model in SDN-enabled large scale cloud data centers, Multimed. Tools Appl., 80, 15541, 10.1007/s11042-021-10616-6 · DOI
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  9. Son, 2013, An SLA-based cloud computing that facilitates resource allocation in the distributed data centers of a cloud provider, J. Supercomput., 64, 606, 10.1007/s11227-012-0861-z · DOI
  10. Barkat, 2018, Green approach for joint management of geo-distributed data centers and interconnection networks, J. Netw. Syst. Manag., 26, 723, 10.1007/s10922-017-9441-0 · DOI
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Metadata

Authors
Rawas, S., Zekri, A., & El-Zaart, A.
Affiliations
Beirut Arab University (LB)
Corresponding author
Rawas, Soha
ORCID
Venue
Sustainable Computing: Informatics and Systems
Publisher
Elsevier BV
Published
2022-01
Volume
33
Pages
100649
ISSN
2210-5379 (ISSN-L)
DOI
10.1016/j.suscom.2021.100649
OpenAlex
W4200406015
Cited by
12
References
0
Citations by year
2025: 4 · 2024: 4 · 2023: 3 · 2022: 1
FWCI
1.81
Type
journal article
Language
en
Open access
closed
Licence
Locations
Sustainable Computing Informatics and Systems (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Cloud Computing and Resource Management
  • Physical Sciences › Computer Science › Hardware and Architecture › Energy Efficiency in Computing
  • Physical Sciences › Computer Science › Computer Networks and Communications › Distributed and Parallel Computing Systems
Keywords
virtual machine placement, geo-distributed data centers, carbon footprint reduction, network latency, virtual machine migration, multi-objective optimization, greedy algorithm, machine learning prediction, cloud computing energy consumption

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