Scalable Virtual Network Mapping Algorithm for Internet-Scale Networks

Qiang YANG  Chunming WU  Min ZHANG  

Publication
IEICE TRANSACTIONS on Communications   Vol.E95-B   No.7   pp.2222-2231
Publication Date: 2012/07/01
Online ISSN: 1745-1345
DOI: 10.1587/transcom.E95.B.2222
Print ISSN: 0916-8516
Type of Manuscript: Special Section PAPER (Special Section on Future Internet Technologies against Present Crises)
Category: 
Keyword: 
virtual networks,  mapping algorithm,  Internet-scale networks,  hierarchical algorithm,  

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Summary: 
The proper allocation of network resources from a common physical substrate to a set of virtual networks (VNs) is one of the key technical challenges of network virtualization. While a variety of state-of-the-art algorithms have been proposed in an attempt to address this issue from different facets, the challenge still remains in the context of large-scale networks as the existing solutions mainly perform in a centralized manner which requires maintaining the overall and up-to-date information of the underlying substrate network. This implies the restricted scalability and computational efficiency when the network scale becomes large. This paper tackles the virtual network mapping problem and proposes a novel hierarchical algorithm in conjunction with a substrate network decomposition approach. By appropriately transforming the underlying substrate network into a collection of sub-networks, the hierarchical virtual network mapping algorithm can be carried out through a global virtual network mapping algorithm (GVNMA) and a local virtual network mapping algorithm (LVNMA) operated in the network central server and within individual sub-networks respectively with their cooperation and coordination as necessary. The proposed algorithm is assessed against the centralized approaches through a set of numerical simulation experiments for a range of network scenarios. The results show that the proposed hierarchical approach can be about 5-20 times faster for VN mapping tasks than conventional centralized approaches with acceptable communication overhead between GVNCA and LVNCA for all examined networks, whilst performs almost as well as the centralized solutions.