Reference : Real-Time Virtual Network Function (VNF) Migration toward Low Network Latency in Clou...

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/34040

Title :	Real-Time Virtual Network Function (VNF) Migration toward Low Network Latency in Cloud Environments
Language :	English
Author, co-author :	Cho, Daewoong [> >]
	Taheri, Javid [> >]
	Zomaya, Albert Y. [> >]
	Bouvry, Pascal [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Publication date :	Jun-2017
Main document title :	IEEE 10th International Conference on Cloud Computing (CLOUD), 2017
Publisher :	IEEE
Peer reviewed :	Yes
Audience :	International
Event name :	Cloud 2017
Event date :	25-30 June 2017
Event organizer :	IEEE
Keywords :	[en] Cloud computing, Heuristic algorithms, Real-time systems, Resource management, Virtual machining, Dynamic scheduling, Electronic mail
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.
Target :	Researchers
Permalink :	http://hdl.handle.net/10993/34040
DOI :	10.1109/CLOUD.2017.118
Other URL :	http://ieeexplore.ieee.org/document/8030676/

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