Meta-heuristic Approaches for Effective Scheduling in Infrastructure as a Service Cloud: A Systematic Review

J. Kok Konjaang; Lina Xu

doi:10.1007/s10922-020-09577-2

Meta-heuristic Approaches for Effective Scheduling in Infrastructure as a Service Cloud: A Systematic Review

Journal of Network and Systems Management ◽

10.1007/s10922-020-09577-2 ◽

2021 ◽

Vol 29 (2) ◽

Author(s):

J. Kok Konjaang ◽

Lina Xu

Keyword(s):

Systematic Review ◽

Infrastructure As A Service ◽

Heuristic Approaches ◽

Service Cloud

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Cost-Efficient and Application SLA-Aware Client Side Request Scheduling in an Infrastructure-as-a-Service Cloud

2012 IEEE Fifth International Conference on Cloud Computing ◽

10.1109/cloud.2012.21 ◽

2012 ◽

Cited By ~ 33

Author(s):

Philipp Leitner ◽

Waldemar Hummer ◽

Benjamin Satzger ◽

Christian Inzinger ◽

Schahram Dustdar

Keyword(s):

Infrastructure As A Service ◽

Cost Efficient ◽

Client Side ◽

Service Cloud

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Semi-Markov's models for availability assessment of an Infrastructure as a Service Cloud with multiple pools of physical and virtual machines

2018 IEEE 9th International Conference on Dependable Systems, Services and Technologies (DESSERT) ◽

10.1109/dessert.2018.8409107 ◽

2018 ◽

Cited By ~ 1

Author(s):

Oleg Ivanchenko ◽

Vyacheslav Kharchenko ◽

Borys Moroz ◽

Leonid Kabak ◽

Kyrylo Smoktii

Keyword(s):

Virtual Machines ◽

Infrastructure As A Service ◽

Availability Assessment ◽

Service Cloud

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Job Scheduling Technique for Infrastructure as a Service Cloud Using an Improved League Championship Algorithm

Proceedings of the International Conference on Data Engineering 2015 (DaEng-2015) - Lecture Notes in Electrical Engineering ◽

10.1007/978-981-13-1799-6_50 ◽

2019 ◽

pp. 479-488

Author(s):

Shafi’i Muhammad Abdulhamid ◽

Muhammad Shafie Abd Latiff ◽

Mohammed Abdullahi

Keyword(s):

Job Scheduling ◽

Infrastructure As A Service ◽

Scheduling Technique ◽

Service Cloud

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A queuing approach to model power and performance trade-off with maintenance overhead of an infrastructure-as-a-service cloud

International Journal of Communication Networks and Distributed Systems ◽

10.1504/ijcnds.2017.083826 ◽

2017 ◽

Vol 18 (3/4) ◽

pp. 287

Author(s):

Srichandan Sobhanayak ◽

Ashok Kumar Turuk ◽

Bibhudatta Sahoo

Keyword(s):

Infrastructure As A Service ◽

Trade Off ◽

And Performance ◽

Service Cloud

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The State of Public Infrastructure-as-a-Service Cloud Security

ACM Computing Surveys ◽

10.1145/2767181 ◽

2015 ◽

Vol 47 (4) ◽

pp. 1-31 ◽

Cited By ~ 30

Author(s):

Wei Huang ◽

Afshar Ganjali ◽

Beom Heyn Kim ◽

Sukwon Oh ◽

David Lie

Keyword(s):

Cloud Security ◽

The State ◽

Public Infrastructure ◽

Infrastructure As A Service ◽

Service Cloud

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An efficient mapping of workflow tasks in infrastructure as a service cloud platforms

2017 2nd International Conference on Communication and Electronics Systems (ICCES) ◽

10.1109/cesys.2017.8321143 ◽

2017 ◽

Author(s):

V Kalpana ◽

R L Janane ◽

S K Kaavya Shree ◽

V Meena

Keyword(s):

Infrastructure As A Service ◽

Workflow Tasks ◽

Service Cloud

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A Generic Logging Template for Infrastructure as a Service Cloud

2013 27th International Conference on Advanced Information Networking and Applications Workshops ◽

10.1109/waina.2013.108 ◽

2013 ◽

Cited By ~ 5

Author(s):

W. Wongthai ◽

F. L. Rocha ◽

A. van Moorsel

Keyword(s):

Infrastructure As A Service ◽

Service Cloud

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JUSUF: Modular Tier-2 Supercomputing and Cloud Infrastructure at Jülich Supercomputing Centre

Journal of large-scale research facilities JLSRF ◽

10.17815/jlsrf-7-179 ◽

2021 ◽

Vol 7 ◽

Author(s):

Benedikt Von St. Vieth

Keyword(s):

Human Brain ◽

Product Family ◽

Research Infrastructure ◽

Tier 2 ◽

Cloud Infrastructure ◽

Infrastructure As A Service ◽

Human Brain Project ◽

Cluster Partition ◽

Cloud Resource ◽

Service Cloud

JUSUF is a petaflop supercomputer operated by Jülich Supercomputing Centre at Forschungszentrum Jülich as a European supercomputing and cloud resource. JUSUF was funded via the ICEI project and especially serves the Human Brain Project and PRACE via ICEI and the Fenix Research Infrastructure. The system consists of two parts, an HPC cluster partition and an Infrastructure-as-a-Service cloud partition. The system entered production phase in spring 2020. It is based on the Bull X400 product family with AMD Rome processors, partially accelerated by Nvidia V100 GPUs, and Nvidia Mellanox HDR InfiniBand.

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