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Towards Understanding Uncertainty in Cloud Computing Resource Provisioning
dc.contributor.author | Tchernykh, Andrei |
dc.contributor.author | Schwiegelsohn, Uwe |
dc.contributor.author | Alexandrov, Vassil |
dc.contributor.author | Talbi, El-ghazali |
dc.contributor.other | Barcelona Supercomputing Center |
dc.date.accessioned | 2016-05-12T10:57:04Z |
dc.date.available | 2016-05-12T10:57:04Z |
dc.date.issued | 2015 |
dc.identifier.citation | Tchernykh, Andrei [et al.]. Towards Understanding Uncertainty in Cloud Computing Resource Provisioning. "Procedia Computer Science", 2015, vol. 51, p. 1772-1781. |
dc.identifier.issn | 1877-0509 |
dc.identifier.uri | http://hdl.handle.net/2117/87002 |
dc.description.abstract | In spite of extensive research of uncertainty issues in different fields ranging from computational biology to decision making in economics, a study of uncertainty for cloud computing systems is limited. Most of works examine uncertainty phenomena in users’ perceptions of the qualities, intentions and actions of cloud providers, privacy, security and availability. But the role of uncertainty in the resource and service provisioning, programming models, etc. have not yet been adequately addressed in the scientific literature. There are numerous types of uncertainties associated with cloud computing, and one should to account for aspects of uncertainty in assessing the efficient service provisioning. In this paper, we tackle the research question: what is the role of uncertainty in cloud computing service and resource provisioning? We review main sources of uncertainty, fundamental approaches for scheduling under uncertainty such as reactive, stochastic, fuzzy, robust, etc. We also discuss potentials of these approaches for scheduling cloud computing activities under uncertainty, and address methods for mitigating job execution time uncertainty in the resource provisioning. |
dc.format.extent | 10 p. |
dc.language.iso | eng |
dc.publisher | Elsevier |
dc.rights | Attribution-NonCommercial-NoDerivs 4.0 International License |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ |
dc.subject | Àrees temàtiques de la UPC::Enginyeria electrònica |
dc.subject.lcsh | Cloud computing |
dc.subject.lcsh | Computational biology |
dc.subject.lcsh | Optimization |
dc.subject.other | Cloud computing |
dc.subject.other | Uncertainty |
dc.subject.other | Resource provisioning |
dc.subject.other | Optimization |
dc.subject.other | Scheduling |
dc.subject.other | Classification |
dc.title | Towards Understanding Uncertainty in Cloud Computing Resource Provisioning |
dc.type | Article |
dc.subject.lemac | Computació en núvol |
dc.subject.lemac | Biologia computacional |
dc.identifier.doi | 10.1016/j.procs.2015.05.387 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://www.sciencedirect.com/science/article/pii/S1877050915011953 |
dc.rights.access | Open Access |
dc.description.version | Postprint (published version) |
local.citation.contributor | International Conference On Computational Science, ICCS 2015 — Computational Science at the Gates of Nature |
local.citation.publicationName | Procedia Computer Science |
local.citation.volume | 51 |
local.citation.startingPage | 1772 |
local.citation.endingPage | 1781 |
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