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Real-time resource ...
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Flinta, C.Ericsson Research, Sweden
(author)
Real-time resource prediction engine for cloud management
- Article/chapterEnglish2017
Publisher, publication year, extent ...
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Institute of Electrical and Electronics Engineers Inc.2017
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printrdacarrier
Numbers
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LIBRIS-ID:oai:DiVA.org:kth-216282
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https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-216282URI
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https://doi.org/10.23919/INM.2017.7987392DOI
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https://urn.kb.se/resolve?urn=urn:nbn:se:ri:diva-38069URI
Supplementary language notes
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Language:English
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Summary in:English
Part of subdatabase
Classification
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Subject category:ref swepub-contenttype
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Subject category:kon swepub-publicationtype
Notes
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QC 20171213
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Predicting resource requirements for cloud services is critical for dimensioning, anomaly detection and service assurance. We demonstrate a system for real-time estimation of the needed amount of infrastructure resources, such as CPU and memory, for a given service. Statistical learning methods on server statistics and load parameters of the service are used for learning a resource prediction model. The model can be used as a guideline for service deployment and for real-time identification of resource bottlenecks.
Subject headings and genre
Added entries (persons, corporate bodies, meetings, titles ...)
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Johnsson, A.Ericsson Research, Sweden
(author)
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Ahmed, J.Ericsson Research, Sweden
(author)
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Moradi, F.Ericsson Research, Sweden
(author)
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Pasquini, R.RISE,SICS,Federal University of Uberlandia, Brazil
(author)
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Stadler, RolfRISE,KTH,ACCESS Linnaeus Centre,SICS,KTH Royal Institute of Technology, Sweden(Swepub:ri)rolf.stadler@ri.se
(author)
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Ericsson Research, SwedenSICS
(creator_code:org_t)
Related titles
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In:Proceedings of the IM 2017 - 2017 IFIP/IEEE International Symposium on Integrated Network and Service Management: Institute of Electrical and Electronics Engineers Inc., s. 877-8789783901882890
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