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dc.contributor.authorKar, Binayaken_US
dc.contributor.authorWu, Eric Hsiao-Kuangen_US
dc.contributor.authorLin, Ying-Daren_US
dc.date.accessioned2018-08-21T05:53:25Z-
dc.date.available2018-08-21T05:53:25Z-
dc.date.issued2018-03-01en_US
dc.identifier.issn1932-4537en_US
dc.identifier.urihttp://dx.doi.org/10.1109/TNSM.2017.2782370en_US
dc.identifier.urihttp://hdl.handle.net/11536/144677-
dc.description.abstractNetwork function virtualization (NFV), with its virtualization technologies, brings cloud computing to networking. Virtualized network functions (VNFs) are chained together to provide the required functionality at runtime on demand. It has a direct impact on power consumption depending on where and how these VNFs are placed and chained to accomplish certain demands as the power consumption of a physical machine (PM) depends on its traffic load. One of the advantages of VNF placement over traditional virtual machine placement is that virtualization is not limited solely to servers. The PMs, including the servers and varying loads to these machines and their utilization, are critical issues related to the network's energy consumption. In this paper, we designed a dynamic energy-saving model with NFV technology using an M/M/c queuing network with the minimum capacity policy where a certain amount of load is required to start the machine, which increases the utilization of the machine and avoids frequent changes of the machines' states. We formulate an energy-cost optimization problem with capacity and delay as constraints. We propose a dynamic placement of VNF chains (DPVC) heuristic solution to the NP-hard problem. The results show that the DPVC solution performs better and saves more energy. It uses 45%-55% less active nodes to satisfy the requested demands and increases the utilization of the active nodes by 40%-50% compared to other algorithms.en_US
dc.language.isoen_USen_US
dc.subjectVirtualized network functionen_US
dc.subjectservice chainingen_US
dc.subjectMarkov modelen_US
dc.subjectenergy consumptionen_US
dc.subjectcost optimizationen_US
dc.titleEnergy Cost Optimization in Dynamic Placement of Virtualized Network Function Chainsen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/TNSM.2017.2782370en_US
dc.identifier.journalIEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENTen_US
dc.citation.volume15en_US
dc.citation.spage372en_US
dc.citation.epage386en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000427420100027en_US
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