Röblitz, Thomas

[["dc.bibliographiccitation.firstpage","288"],["dc.bibliographiccitation.lastpage","295"],["dc.contributor.author","Lu, Kuan"],["dc.contributor.author","Röblitz, Thomas"],["dc.contributor.author","Yahyapour, Ramin"],["dc.contributor.author","Yaqub, Edwin"],["dc.contributor.author","Kotsokalis, Constantinos"],["dc.date.accessioned","2019-02-18T10:01:20Z"],["dc.date.available","2019-02-18T10:01:20Z"],["dc.date.issued","2011"],["dc.description.abstract","Cloud computing effectively implements the vision of utility computing by employing a pay-as-you-go cost model and allowing on-demand (re-)leasing of IT resources. Small or medium-sized Infrastructure-as-a-Service providers, however, find it challenging to satisfy all requests immediately due to their limited resource capacity. In that situation, both providers and customers may benefit greatly from advanced reservation of virtual resources, i.e. virtual machines. In our work, we assume SLA-based resource requests and introduce an advanced reserva- tion methodology during SLA negotiation by using computational geometry. Thereby, we are able to verify, record and manage the infrastructure resources efficiently. Based on that model, service providers can easily verify the available capacity for satisfying the customer’s Quality-of-Service requirements. Furthermore, we introduce flexible alternative counter-offers, when the service provider lacks resources. Therefore, our mechanism increases the utilization of the resources and attempts to satisfy as many customers as possible."],["dc.identifier.doi","10.1109/CloudCom.2011.46"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/57574"],["dc.language.iso","en"],["dc.notes.preprint","yes"],["dc.notes.status","final"],["dc.relation.conference","IEEE 3rd International Conference on Cloud Computing Technology and Science, CloudCom 2011"],["dc.relation.eventend","2011-12-01"],["dc.relation.eventlocation","Athens, Greece"],["dc.relation.eventstart","2011-11-29"],["dc.relation.isbn","978-1-4673-0090-2"],["dc.relation.iserratumof","yes"],["dc.relation.orgunit","Gesellschaft für wissenschaftliche Datenverarbeitung"],["dc.title","QoS-aware SLA-based Advanced Reservation of Infrastructure as a Service"],["dc.type","conference_paper"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","325"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Journal of Grid Computing"],["dc.bibliographiccitation.lastpage","346"],["dc.bibliographiccitation.volume","10"],["dc.contributor.author","Hirales-Carbajal, Adán"],["dc.contributor.author","Tchernykh, Andrei"],["dc.contributor.author","Yahyapour, Ramin"],["dc.contributor.author","González-García, José Luis"],["dc.contributor.author","Röblitz, Thomas"],["dc.contributor.author","Ramírez-Alcaraz, Juan Manuel"],["dc.date.accessioned","2018-08-16T14:09:31Z"],["dc.date.available","2018-08-16T14:09:31Z"],["dc.date.issued","2012"],["dc.description.abstract","In this paper, we present an experimental study of deterministic non-preemptive multiple workflow scheduling strategies on a Grid. We distinguish twenty five strategies depending on the type and amount of information they require. We analyze scheduling strategies that consist of two and four stages: labeling, adaptive allocation, prioritization, and parallel machine scheduling. We apply these strategies in the context of executing the Cybershake, Epigenomics, Genome, Inspiral, LIGO, Montage, and SIPHT workflows applications. In order to provide performance comparison, we performed a joint analysis considering three metrics. A case study is given and corresponding results indicate that well known DAG scheduling algorithms designed for single DAG and single machine settings are not well suited for Grid scheduling scenarios, where user run time estimates are available. We show that the proposed new strategies outperform other strategies in terms of approximation factor, mean critical path waiting time, and critical path slowdown. The robustness of these strategies is also discussed."],["dc.identifier.doi","10.1007/s10723-012-9215-6"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/15374"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.relation.eissn","1572-9184"],["dc.relation.issn","1570-7873"],["dc.relation.orgunit","Gesellschaft für wissenschaftliche Datenverarbeitung"],["dc.title","Multiple Workflow Scheduling Strategies with User Run Time Estimates on a Grid"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]