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AuthorCastañé, Gabriel Gonzá
AuthorByrne, Peter
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AbstractSince the arrival of cloud computing, a significant amount of research has been and continues to be carried out towards the creation of efficient optimisation strategies for meeting certain optimisation goals such as energy efficiency, resource consolidation or performance improvement within virtualised data centres. However, investigating whether specific optimisation algorithms can achieve the desired function in a production environment, and investigating how well they operate are quite complex tasks. Untested optimisation rules typically cannot be directly deployed in the production system, instead requiring manual test-bed experiments. This technique can be prohibitively costly, time consuming and cannot always account for scale and other constraints. This work presents a design-time optimisation evaluation solution based on discrete event simulation for cloud computing. By using a simulation toolkit (CactoSim) coupled with a runtime optimisation toolkit (CactoOpt), a cloud architect is able to create a direct replica model of the data centre production environment and then run simulations which take into account optimisation strategies. Results produced by such simulations can be used to estimate the optimisation algorithm performance under various conditions. With CACTOS addressing the efficient management of IaaS data centres running Scientific Computing, Business Analytics and White-Box applications, the CACTOS Prediction Toolkit supports design time decision-making via simulation for each of these areas. Typical scenarios for each of the three use cases of scientific computing, business analytics and white box applications have been modelled, run and analysed using simulation, taking the optimisation algorithms into account, and these are presented in this document. This deliverable represents the final part of two iterative pieces of work.dc.description.abstract
PublisherUniversität Ulmdc.publisher
LicenseCC BY-ND 4.0 Internationaldc.rights
Link to license text
KeywordData managementdc.subject
KeywordContext-aware cloud topologydc.subject
KeywordCloud servicesdc.subject
Dewey Decimal GroupDDC 004 / Data processing & computer sciencedc.subject.ddc
LCSHCloud computingdc.subject.lcsh
LCSHElectric network topologydc.subject.lcsh
TitleFinal results from optimisation models validation and experimentation: project deliverable D6.5dc.title
Resource typeBerichtdc.type
GNDCloud Computingdc.subject.gnd
FacultyFakultät für Ingenieurwissenschaften, Informatik und Psychologieuulm.affiliationGeneral
InstitutionInstitut für Organisation und Management von Informationssystemenuulm.affiliationSpecific
DCMI TypeTextuulm.typeDCMI
In cooperation withDublin City Universityuulm.cooperation
In cooperation withFZI Forschungszentrum Informatik am Karlsruher Institut für Technologieuulm.cooperation
In cooperation withUmeå Universitetuulm.cooperation
EU projectCACTOS / Context-Aware Cloud Topology Optimisation and Simulation / EC / FP7 / 610711uulm.projectEU
FundingEC / FP7uulm.funding

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CC BY-ND 4.0 International
Except where otherwise noted, this item's license is described as CC BY-ND 4.0 International