Data for: Dynamic Virtual Machine Consolidation using a multi-agent system to optimise energy efficiency in Cloud Computing

Published: 3 Mar 2020 | Version 1 | DOI: 10.17632/bg36grn6nx.1
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Description of this data

This dataset covers five data components of interest developed during our research which is published in “Dynamic Virtual Machine Consolidation using a multi-agent system to optimise energy efficiency in Cloud Computing”. They are: a patch file, peersim-1.0.5-nmcd.patch, for PeerSim version 1.0.5; four zip files contains the source code for the Gossip Contracts framework, GossipContracts-src.zip, the DVMC models, DVMC-src.zip, the module to process the Google dataset, GoogleTraceData-src.zip, and some utility methods, Util-src.zip; and the experiment results files, ResearchData-Results.zip.

Experiment data files

This data is associated with the following publication:

Dynamic virtual machine consolidation using a multi-agent system to optimise energy efficiency in cloud computing

Published in: Future Generation Computer Systems

Latest version

  • Version 1

    2020-03-03

    Published: 2020-03-03

    DOI: 10.17632/bg36grn6nx.1

    Cite this dataset

    Mc Donnell, Nicola; Howley, Enda; Duggan, Jim (2020), “Data for: Dynamic Virtual Machine Consolidation using a multi-agent system to optimise energy efficiency in Cloud Computing”, Mendeley Data, v1 http://dx.doi.org/10.17632/bg36grn6nx.1

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Computer Industry

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CC BY 4.0 Learn more

The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.

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You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.

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