Virtual routers on the move: live router migration as a network-management primitive
Proceedings of the ACM SIGCOMM 2008 conference on Data communication
On dominant characteristics of residential broadband internet traffic
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
A survey of network virtualization
Computer Networks: The International Journal of Computer and Telecommunications Networking
Characterizing and modeling internet traffic dynamics of cellular devices
ACM SIGMETRICS Performance Evaluation Review - Performance evaluation review
Latency inflation with MPLS-based traffic engineering
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Online strategies for intra and inter provider service migration in virtual networks
IPTcomm '11 Proceedings of the 5th International Conference on Principles, Systems and Applications of IP Telecommunications
Uncovering the big players of the web
TMA'12 Proceedings of the 4th international conference on Traffic Monitoring and Analysis
Internet access traffic measurement and analysis
TMA'12 Proceedings of the 4th international conference on Traffic Monitoring and Analysis
Live migration of an entire network (and its hosts)
Proceedings of the 11th ACM Workshop on Hot Topics in Networks
A cost efficient framework and algorithm for embedding dynamic virtual network requests
Future Generation Computer Systems
IEEE Internet Computing
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Virtual Network Embedding (VNE) algorithms are used to find the best embedding of multiple Virtual Networks (VNs) with respect to a performance metric such as network utilization. However, most algorithms assume that the demands of the VNs are static over time. We focus on VNE algorithms for VNs whose demands are changing according to traffic patterns of their provided services. In order to always guarantee high performance and network resource efficiency, the embedding of the VNs has to change, i.e., the VNs have to be re-embedded. By considering traffic patterns of different services, we propose an algorithm that looks ahead and minimize the impact of reconfigurations that are the result of a re-embedding. First simulation results show the potential of VNE algorithms that consider the behavior of evolving service demands.