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IC-PCP profiling: software and data set

Taal, Arie; Wang, Junchao; de Laat, Cees; Zhao, Zhiming


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  <identifier identifierType="DOI">10.5281/zenodo.2652669</identifier>
  <creators>
    <creator>
      <creatorName>Taal, Arie</creatorName>
      <givenName>Arie</givenName>
      <familyName>Taal</familyName>
      <affiliation>University of Amsterdam</affiliation>
    </creator>
    <creator>
      <creatorName>Wang, Junchao</creatorName>
      <givenName>Junchao</givenName>
      <familyName>Wang</familyName>
      <affiliation>University of Amsterdam</affiliation>
    </creator>
    <creator>
      <creatorName>de Laat, Cees</creatorName>
      <givenName>Cees</givenName>
      <familyName>de Laat</familyName>
      <affiliation>University of Amsterdam</affiliation>
    </creator>
    <creator>
      <creatorName>Zhao, Zhiming</creatorName>
      <givenName>Zhiming</givenName>
      <familyName>Zhao</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-6717-9418</nameIdentifier>
      <affiliation>University of Amsterdam</affiliation>
    </creator>
  </creators>
  <titles>
    <title>IC-PCP profiling: software and data set</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <subjects>
    <subject>IC-PCP</subject>
    <subject>Profiling</subject>
    <subject>Cloud</subject>
    <subject>Time critical application</subject>
    <subject>Critical paths</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2019-04-16</date>
  </dates>
  <resourceType resourceTypeGeneral="Software"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/2652669</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.2652668</relatedIdentifier>
  </relatedIdentifiers>
  <version>version 4-16-2019</version>
  <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;pre&gt;We study the scheduling decisions for handling deadline-constrained workflows in the context of planning customized virtual infrastructures in the cloud. We specifically focus on the effects of using different types of greediness in selecting cost-effective virtual machines for the tasks in an application&amp;#39;s workflow graph. The profiling procedure followed demonstrates that for the widely used approach of the partial critical path algorithm a greedy version is preferred to a more stringent version under different stress conditions, from tight to loose deadlines. Representative topologies of workflow applications are used to generate sets of task graph scheduling problems. &lt;/pre&gt;

&lt;pre&gt;Monitoring the performance of the partial critical path algorithm with different types of greediness reveals which of the topologies tested are difficult to solve under various stress conditions.&lt;/pre&gt;

&lt;pre&gt;It turns out that an invalid outcome of a greedy version of the partial critical path algorithm is more susceptible to become valid via a final refinement cycle than a less greedy version. The procedure outlined in this paper will allow for a systematic study of a specific heuristic in a workflow scheduling method to increase its success in infrastructure planning under different deadline conditions and is proposed to be part of a general profiling framework.&lt;/pre&gt;

&lt;pre&gt;All four implementations of the IC-PCP algorithm used in this study as well as the data to produce the performance figures are available at https://bitbucket.org/uva-sne/ic-pcp-profiling/src/master.&lt;/pre&gt;</description>
    <description descriptionType="Other">This research has received funding from the European Union's Horizon 2020 research and innovation program under grant agreements 643963 (SWITCH project), 654182 (ENVRIPLUS project), 676247 (VRE4EIC project), 824068(ENVRI-FAIR project) and 825134(ARTICONF project).</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/676247/">676247</awardNumber>
      <awardTitle>A Europe-wide Interoperable Virtual Research Environment to Empower Multidisciplinary Research Communities and Accelerate Innovation and Collaboration</awardTitle>
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    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/654182/">654182</awardNumber>
      <awardTitle>Environmental Research Infrastructures Providing Shared Solutions for Science and Society</awardTitle>
    </fundingReference>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/643963/">643963</awardNumber>
      <awardTitle>Software Workbench for Interactive, Time Critical and Highly self-adaptive cloud applications</awardTitle>
    </fundingReference>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/825134/">825134</awardNumber>
      <awardTitle>smART socIal media eCOsytstem in a blockchaiN Federated environment</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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