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dc.contributor.authorRen, Yien_US
dc.contributor.authorTuan Phung-Ducen_US
dc.contributor.authorLiu, Yi-Kuanen_US
dc.contributor.authorChen, Jyh-Chengen_US
dc.contributor.authorLin, Yi-Haoen_US
dc.date.accessioned2019-06-03T01:09:17Z-
dc.date.available2019-06-03T01:09:17Z-
dc.date.issued2018-01-01en_US
dc.identifier.isbn978-1-5386-6831-3en_US
dc.identifier.issn2374-3239en_US
dc.identifier.urihttp://hdl.handle.net/11536/152031-
dc.description.abstract5G mobile networks introduce Virtualized Network Functions (VNFs) to provide flexible services for incoming huge mobile data traffic. Compared with fixed capacity legacy network equipment, VNFs can be scaled in/out to adjust system capacity. However, hardware-based legacy network equipment is designed dedicatedly for its purpose so that it is more efficient in terms of unit cost. One challenge is to best use VNF resources and to balance the traffic between legacy network equipment and VNFs. To address this challenge, we first formulate the problem as a cost-performance tradeoff, where both VNF resource cost and system performance are quantified. Then, we propose an adaptive VNF scaling algorithm to balance the tradeoff. We derive the suitable VNF instances to handle data traffic with minimizing cost. Through extensive simulations, the adaptive algorithm is proven to provide good performance.en_US
dc.language.isoen_USen_US
dc.subjectDynamic Auto Scaling Algorithmen_US
dc.subjectNetwork Function Virtualization (NFV)en_US
dc.subjectVirtual EPCen_US
dc.subjectCloud Networksen_US
dc.subject5Gen_US
dc.subjectModeling and Analysisen_US
dc.titleASA: Adaptive VNF Scaling Algorithm for 5G Mobile Networksen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2018 IEEE 7TH INTERNATIONAL CONFERENCE ON CLOUD NETWORKING (CLOUDNET)en_US
dc.citation.spage0en_US
dc.citation.epage0en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000465081600046en_US
dc.citation.woscount0en_US
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