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Virtual Network Function Placement: Towards Minimizing Network Latency and Lead Time
Univ. of Sydney, Sydney, NSW, Australia.
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (from 2013). (DISCO, Computer Networking)ORCID-id: 0000-0001-9194-010X
School of Information Technologies, University of Sydney.
China Univ. of Geosci., China.
2017 (engelsk)Inngår i: 2017 IEEE International Conference on Cloud Computing Technology and Science (CloudCom), Piscataway: IEEE, 2017, s. 90-97Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Network Function Virtualization (NFV) is an emerging network architecture to increase flexibility and agility within operator's networks by placing virtualized services on demand in Cloud data centers (CDCs). One of the main challenges for the NFV environment is how to minimize network latency in the rapidly changing network environments. Although many researchers have already studied in the field of Virtual Machine (VM) migration and Virtual Network Function (VNF) placement for efficient resource management in CDCs, VNF migration problem for low network latency among VNFs has not been studied yet to the best of our knowledge. To address this issue in this article, we i) formulate the VNF migration problem and ii) develop a novel VNF migration algorithm called VNF Real-time Migration (VNF-RM) for lower network latency in dynamically changing resource availability. As a result of experiments, the effectiveness of our algorithm is demonstrated by reducing network latency by up to 70.90% after latency-aware VNF migrations.

sted, utgiver, år, opplag, sider
Piscataway: IEEE, 2017. s. 90-97
Serie
IEEE International Conference on Cloud Computing, CLOUD, ISSN 2159-6182, E-ISSN 2159-6190
Emneord [en]
Network Function Virtualization, Virtual Network Function, Virtual Network Function Placement
HSV kategori
Forskningsprogram
Datavetenskap
Identifikatorer
URN: urn:nbn:se:kau:diva-66137DOI: 10.1109/CLOUD.2017.12ISI: 000427727800012ISBN: 978-1-5386-1993-3 (digital)ISBN: 978-1-5386-1994-0 (tryckt)OAI: oai:DiVA.org:kau-66137DiVA, id: diva2:1180729
Konferanse
9th IEEE International Conference on Cloud Computing Technology and Science, 11-14 December 2017, Hong Kong
Tilgjengelig fra: 2018-02-06 Laget: 2018-02-06 Sist oppdatert: 2019-11-10bibliografisk kontrollert

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