Conference paper Open Access

SheerMP: Optimized Streaming Analytics-as-a-Service over Multi-site Multi-platform Settings

George Stamatakis; Antonios Kontaxakis; Alkis Simitsis; Nikos Giatrakos; Antonios Deligiannakis


DCAT Export

<?xml version='1.0' encoding='utf-8'?>
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:adms="http://www.w3.org/ns/adms#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dct="http://purl.org/dc/terms/" xmlns:dctype="http://purl.org/dc/dcmitype/" xmlns:dcat="http://www.w3.org/ns/dcat#" xmlns:duv="http://www.w3.org/ns/duv#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:frapo="http://purl.org/cerif/frapo/" xmlns:geo="http://www.w3.org/2003/01/geo/wgs84_pos#" xmlns:gsp="http://www.opengis.net/ont/geosparql#" xmlns:locn="http://www.w3.org/ns/locn#" xmlns:org="http://www.w3.org/ns/org#" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:prov="http://www.w3.org/ns/prov#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns:schema="http://schema.org/" xmlns:skos="http://www.w3.org/2004/02/skos/core#" xmlns:vcard="http://www.w3.org/2006/vcard/ns#" xmlns:wdrs="http://www.w3.org/2007/05/powder-s#">
  <rdf:Description rdf:about="https://doi.org/10.5281/zenodo.6345357">
    <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#anyURI">https://doi.org/10.5281/zenodo.6345357</dct:identifier>
    <foaf:page rdf:resource="https://doi.org/10.5281/zenodo.6345357"/>
    <dct:creator>
      <rdf:Description>
        <rdf:type rdf:resource="http://xmlns.com/foaf/0.1/Agent"/>
        <foaf:name>George Stamatakis</foaf:name>
        <org:memberOf>
          <foaf:Organization>
            <foaf:name>Athena Research Center</foaf:name>
          </foaf:Organization>
        </org:memberOf>
      </rdf:Description>
    </dct:creator>
    <dct:creator>
      <rdf:Description>
        <rdf:type rdf:resource="http://xmlns.com/foaf/0.1/Agent"/>
        <foaf:name>Antonios Kontaxakis</foaf:name>
        <org:memberOf>
          <foaf:Organization>
            <foaf:name>Universite Libre de Bruxelles &amp; Athena Research Center</foaf:name>
          </foaf:Organization>
        </org:memberOf>
      </rdf:Description>
    </dct:creator>
    <dct:creator>
      <rdf:Description>
        <rdf:type rdf:resource="http://xmlns.com/foaf/0.1/Agent"/>
        <foaf:name>Alkis Simitsis</foaf:name>
        <org:memberOf>
          <foaf:Organization>
            <foaf:name>Athena Research Center</foaf:name>
          </foaf:Organization>
        </org:memberOf>
      </rdf:Description>
    </dct:creator>
    <dct:creator>
      <rdf:Description rdf:about="http://orcid.org/0000-0002-8218-707X">
        <rdf:type rdf:resource="http://xmlns.com/foaf/0.1/Agent"/>
        <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#string">0000-0002-8218-707X</dct:identifier>
        <foaf:name>Nikos Giatrakos</foaf:name>
        <org:memberOf>
          <foaf:Organization>
            <foaf:name>Athena Research Center &amp; Technical University of Crete</foaf:name>
          </foaf:Organization>
        </org:memberOf>
      </rdf:Description>
    </dct:creator>
    <dct:creator>
      <rdf:Description>
        <rdf:type rdf:resource="http://xmlns.com/foaf/0.1/Agent"/>
        <foaf:name>Antonios Deligiannakis</foaf:name>
        <org:memberOf>
          <foaf:Organization>
            <foaf:name>Athena Research Center &amp; Technical University of Crete</foaf:name>
          </foaf:Organization>
        </org:memberOf>
      </rdf:Description>
    </dct:creator>
    <dct:title>SheerMP: Optimized Streaming Analytics-as-a-Service over Multi-site Multi-platform Settings</dct:title>
    <dct:publisher>
      <foaf:Agent>
        <foaf:name>Zenodo</foaf:name>
      </foaf:Agent>
    </dct:publisher>
    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#gYear">2022</dct:issued>
    <dcat:keyword>Big Data</dcat:keyword>
    <dcat:keyword>Optimization</dcat:keyword>
    <dcat:keyword>Data Streams</dcat:keyword>
    <dcat:keyword>Resource Allocation</dcat:keyword>
    <dcat:keyword>Analytics-as-a-Service</dcat:keyword>
    <dcat:keyword>Software Architectures</dcat:keyword>
    <dcat:keyword>Apache Flink</dcat:keyword>
    <dcat:keyword>Apache Spark</dcat:keyword>
    <dcat:keyword>Apache Kafka</dcat:keyword>
    <frapo:isFundedBy rdf:resource="info:eu-repo/grantAgreement/EC/H2020/825070/"/>
    <schema:funder>
      <foaf:Organization>
        <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#string">10.13039/100010661</dct:identifier>
        <foaf:name>European Commission</foaf:name>
      </foaf:Organization>
    </schema:funder>
    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#date">2022-03-29</dct:issued>
    <dct:language rdf:resource="http://publications.europa.eu/resource/authority/language/ENG"/>
    <owl:sameAs rdf:resource="https://zenodo.org/record/6345357"/>
    <adms:identifier>
      <adms:Identifier>
        <skos:notation rdf:datatype="http://www.w3.org/2001/XMLSchema#anyURI">https://zenodo.org/record/6345357</skos:notation>
        <adms:schemeAgency>url</adms:schemeAgency>
      </adms:Identifier>
    </adms:identifier>
    <dct:isVersionOf rdf:resource="https://doi.org/10.5281/zenodo.6345356"/>
    <dct:isPartOf rdf:resource="https://zenodo.org/communities/infore-project"/>
    <dct:description>&lt;p&gt;Analytics are in the core of many emerging applications and can greatly benefit from the abundance of data and the progress in the processing capabilities of modern hardware. Still, new challenges arise with the extreme complexity of deciding how to execute analytics workflows given the plethora of choices of various cloud providers, the fragmented nature of diverse Big Data technologies, and the difficult task of resource provisioning to dynamically satisfy the demands of running streaming analytics over time. In this paper, we demonstrate a prototype system that optimizes streaming analytics workflows across Big Data platforms and computer clusters. Our system is the first that (i) considers a multi-user setup, (ii) examines the availability of multiple (potentially, geo-dispersed) compute choices, and (iii) provides a holistic framework covering a wide variety of practical optimization and adaptive resource allocation scenarios over a variety of streaming Big Data platforms&lt;/p&gt;</dct:description>
    <dct:accessRights rdf:resource="http://publications.europa.eu/resource/authority/access-right/PUBLIC"/>
    <dct:accessRights>
      <dct:RightsStatement rdf:about="info:eu-repo/semantics/openAccess">
        <rdfs:label>Open Access</rdfs:label>
      </dct:RightsStatement>
    </dct:accessRights>
    <dct:license rdf:resource="https://creativecommons.org/licenses/by/4.0/legalcode"/>
    <dcat:distribution>
      <dcat:Distribution>
        <dcat:accessURL rdf:resource="https://doi.org/10.5281/zenodo.6345357"/>
        <dcat:byteSize>1691090</dcat:byteSize>
        <dcat:downloadURL rdf:resource="https://zenodo.org/record/6345357/files/edbt2022.pdf"/>
        <dcat:mediaType>application/pdf</dcat:mediaType>
      </dcat:Distribution>
    </dcat:distribution>
  </rdf:Description>
  <foaf:Project rdf:about="info:eu-repo/grantAgreement/EC/H2020/825070/">
    <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#string">825070</dct:identifier>
    <dct:title>Interactive Extreme-Scale Analytics and Forecasting</dct:title>
    <frapo:isAwardedBy>
      <foaf:Organization>
        <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#string">10.13039/100010661</dct:identifier>
        <foaf:name>European Commission</foaf:name>
      </foaf:Organization>
    </frapo:isAwardedBy>
  </foaf:Project>
</rdf:RDF>
32
19
views
downloads
All versions This version
Views 3232
Downloads 1919
Data volume 32.1 MB32.1 MB
Unique views 2525
Unique downloads 1818

Share

Cite as