Dataset Open Access

Autonomic Provisioning and Application Mapping on Spot Cloud Resources

Dubois, Daniel J.; Casale, Giuliano


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  <identifier identifierType="DOI">10.5281/zenodo.20281</identifier>
  <creators>
    <creator>
      <creatorName>Dubois, Daniel J.</creatorName>
      <givenName>Daniel J.</givenName>
      <familyName>Dubois</familyName>
      <affiliation>Imperial College London</affiliation>
    </creator>
    <creator>
      <creatorName>Casale, Giuliano</creatorName>
      <givenName>Giuliano</givenName>
      <familyName>Casale</familyName>
      <affiliation>Imperial College London</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Autonomic Provisioning and Application Mapping on Spot Cloud Resources</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2015</publicationYear>
  <dates>
    <date dateType="Issued">2015-09-21</date>
  </dates>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/20281</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="Handle" relationType="IsSupplementTo">10044/1/25102</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;1. Attached files:&amp;nbsp;&amp;nbsp; &amp;nbsp;&amp;nbsp;&amp;nbsp; &amp;nbsp;&lt;/p&gt;

&lt;p&gt;500_100_fmincon_0.95_1.mat&amp;nbsp;&amp;nbsp; &amp;nbsp;&lt;br /&gt;
Experiment with 500 users, 100ms max response time, 95% availability, exact algorithm.&lt;/p&gt;

&lt;p&gt;500_100_heuristic_0.95_1.mat&lt;br /&gt;
Experiment with 500 users, 100ms max response time, 95% availability, our algorithm.&lt;/p&gt;

&lt;p&gt;2000_70_fmincon_0.95_1.mat&lt;br /&gt;
Experiment with 2000 users, 70ms max response time, 95% availability, exact algorithm.&lt;/p&gt;

&lt;p&gt;2000_70_heuristic_0.95_1.mat&lt;br /&gt;
Experiment with 2000 users, 70ms max response time, 95% availability, our algorithm.&lt;/p&gt;

&lt;p&gt;2000_100_fmincon_0.9_1.mat&lt;br /&gt;
Experiment with 2000 users, 100ms max response time, 90% availability, exact algorithm.&lt;/p&gt;

&lt;p&gt;2000_100_heuristic_0.9_1.mat &amp;nbsp; &amp;nbsp;&lt;br /&gt;
Experiment with 2000 users, 100ms max response time, 90% availability, our algorithm.&lt;/p&gt;

&lt;p&gt;2000_100_fmincon_0.95_1.mat &amp;nbsp; &amp;nbsp;&amp;nbsp;&lt;br /&gt;
Experiment with 2000 users, 100ms max response time, 95% availability, exact algorithm.&lt;/p&gt;

&lt;p&gt;2000_100_heuristic_0.95_1.mat &amp;nbsp;&amp;nbsp;&lt;br /&gt;
Experiment with 2000 users, 100ms max response time, 95% availability, our algorithm.&lt;/p&gt;

&lt;p&gt;2000_100_fmincon_0.999_1.mat &amp;nbsp; &amp;nbsp;&lt;br /&gt;
Experiment with 2000 users, 100ms max response time, 99.9% availability, exact algorithm.&lt;/p&gt;

&lt;p&gt;2000_100_heuristic_0.999_1.mat &amp;nbsp;&lt;br /&gt;
Experiment with 2000 users, 100ms max response time, 99.9% availability, our algorithm.&lt;/p&gt;

&lt;p&gt;2000_300_fmincon_0.95_1.mat &amp;nbsp; &amp;nbsp;&amp;nbsp;&lt;br /&gt;
Experiment with 2000 users, 300ms max response time, 95% availability, exact algorithm.&lt;/p&gt;

&lt;p&gt;2000_300_heuristic_0.95_1.mat&amp;nbsp;&lt;br /&gt;
Experiment with 2000 users, 300ms max response time, 95% availability, our algorithm.&lt;/p&gt;

&lt;p&gt;10000_100_fmincon_0.95_1.mat &amp;nbsp; &amp;nbsp;&lt;br /&gt;
Experiment with 10000 users, 100ms max response time, 95% availability, exact algorithm.&lt;/p&gt;

&lt;p&gt;10000_100_heuristic_0.95_1.mat &amp;nbsp;&lt;br /&gt;
Experiment with 10000 users, 100ms max response time, 95% availability, our algorithm.&lt;/p&gt;

&lt;p&gt;2. Data format:&lt;/p&gt;

&lt;p&gt;MATLAB data format, can be load from MATLAB using the following command:&lt;/p&gt;

&lt;p&gt;results = load(filename);&lt;/p&gt;

&lt;p&gt;results is defined as a structure with the following fields:&lt;/p&gt;

&lt;p&gt;results.cost&lt;br /&gt;
&amp;nbsp;&amp;nbsp; &amp;nbsp;Type:&amp;nbsp;&amp;nbsp; &amp;nbsp;scalar, positive real number.&lt;br /&gt;
&amp;nbsp;&amp;nbsp; &amp;nbsp;Desc:&amp;nbsp;&amp;nbsp; &amp;nbsp;hourly cost in US dollars.&lt;/p&gt;

&lt;p&gt;&amp;nbsp;&amp;nbsp; &amp;nbsp;&amp;nbsp;&amp;nbsp; &amp;nbsp;&lt;br /&gt;
results.time&lt;br /&gt;
&amp;nbsp;&amp;nbsp; &amp;nbsp;Type:&amp;nbsp;&amp;nbsp; &amp;nbsp;scalar, positive real number.&lt;br /&gt;
&amp;nbsp;&amp;nbsp; &amp;nbsp;Desc:&amp;nbsp;&amp;nbsp; &amp;nbsp;total time (in seconds) needed by the algorithm to compute the solution.&lt;/p&gt;

&lt;p&gt;results.evaluations&lt;br /&gt;
&amp;nbsp;&amp;nbsp; &amp;nbsp;Type:&amp;nbsp;&amp;nbsp; &amp;nbsp;scalar, positive integer number.&lt;br /&gt;
&amp;nbsp;&amp;nbsp; &amp;nbsp;Desc:&amp;nbsp;&amp;nbsp; &amp;nbsp;number of constraints evaluations needed by the algorithm to compute the&amp;nbsp;&lt;br /&gt;
&amp;nbsp;&amp;nbsp; &amp;nbsp;&amp;nbsp;&amp;nbsp; &amp;nbsp;solution.&lt;/p&gt;

&lt;p&gt;&lt;br /&gt;
results.d&lt;br /&gt;
&amp;nbsp;&amp;nbsp; &amp;nbsp;Type:&amp;nbsp;&amp;nbsp; &amp;nbsp;matrix, non negative positive real number.&amp;nbsp;&lt;br /&gt;
&amp;nbsp;&amp;nbsp; &amp;nbsp;Desc:&amp;nbsp;&amp;nbsp; &amp;nbsp;association matrix between rented resources (columns) and application&amp;nbsp;&lt;br /&gt;
&amp;nbsp;&amp;nbsp; &amp;nbsp;&amp;nbsp;&amp;nbsp; &amp;nbsp;components (rows). The sum of all the elements of this matrix is equal to&lt;br /&gt;
&amp;nbsp;&amp;nbsp; &amp;nbsp;&amp;nbsp;&amp;nbsp; &amp;nbsp;the ECUs used by the application.&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/100011102</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/FP7/629982/">629982</awardNumber>
      <awardTitle>Self-organizing Performance Prediction and Optimization for Large-scale Software Systems</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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