<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:contributor>Binder, Walter</dc:contributor>
  <dc:creator>Björkqvist, Mathias</dc:creator>
  <dc:date>2015-02-11</dc:date>
  <dc:description xmlns:ns0="xml" ns0:lang="en">Service providers seek scalable and cost-effective cloud solutions for hosting their  applications. Despite significant recent advances facilitating the deployment and  management of services on cloud platforms, a number of challenges still remain. Service  providers are confronted with time-varying requests for the provided applications, inter- dependencies between different components, performance variability of the procured  virtual resources, and cost structures that differ from conventional data centers.  Moreover, fulfilling service level agreements, such as the throughput and response time  percentiles, becomes of paramount importance for ensuring business advantages.In this  thesis, we explore service provisioning in clouds from multiple points of view. The aim is to  best provide service replicas in the form of VMs to various service applications, such that  their tail throughput and tail response times, as well as resource utilization, meet the  service level agreements in the most cost effective manner. In particular, we develop  models, algorithms and replication strategies that consider multi-tier composed services  provisioned in clouds. We also investigate how a service provider can opportunistically  take advantage of observed performance variability in the cloud. Finally, we provide  means of guaranteeing tail throughput and response times in the face of performance  variability of VMs, using Markov chain modeling and large deviation theory. We employ  methods from analytical modeling, event-driven simulations and experiments. Overall, this  thesis provides not only a multi-faceted approach to exploring several crucial aspects of  hosting services in clouds, i.e., cost, tail throughput, and tail response times, but our  proposed resource management strategies are also rigorously validated via trace-driven  simulation and extensive experiments</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>https://susi.usi.ch/global/documents/318521</dc:identifier>
  <dc:identifier>https://n2t.net/ark:/12658/srd1318521</dc:identifier>
  <dc:identifier>https://susi.usi.ch/documents/318521/files/2015INFO005.pdf</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:rero-006-114157</dc:relation>
  <dc:relation>info:eu-repo/semantics/altIdentifier/ark/12658/srd1318521</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>License undefined</dc:rights>
  <dc:subject xmlns:ns1="xml" ns1:lang="en">Resource provisioning</dc:subject>
  <dc:subject xmlns:ns2="xml" ns2:lang="en">Cloud</dc:subject>
  <dc:subject xmlns:ns3="xml" ns3:lang="en">Services</dc:subject>
  <dc:subject xmlns:ns4="xml" ns4:lang="en">Resource management</dc:subject>
  <dc:subject xmlns:ns5="xml" ns5:lang="en">Tail throughput</dc:subject>
  <dc:subject xmlns:ns6="xml" ns6:lang="en">Tail response time</dc:subject>
  <dc:subject>info:eu-repo/classification/udc/004</dc:subject>
  <dc:title xmlns:ns7="xml" ns7:lang="en">Resource management of replicated service systems provisioned in the cloud</dc:title>
  <dc:type>http://purl.org/coar/resource_type/c_db06</dc:type>
</oai_dc:dc>