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Virtual network embedding on massive substrate networks
Author(s) -
Zhao Chenggui,
Parhami Behrooz
Publication year - 2020
Publication title -
transactions on emerging telecommunications technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.366
H-Index - 47
ISSN - 2161-3915
DOI - 10.1002/ett.3849
Subject(s) - node (physics) , embedding , overhead (engineering) , ranking (information retrieval) , computer science , rank (graph theory) , virtual network , function (biology) , scheme (mathematics) , topology (electrical circuits) , boundary (topology) , theoretical computer science , mathematics , distributed computing , mathematical optimization , artificial intelligence , combinatorics , engineering , mathematical analysis , structural engineering , evolutionary biology , biology , operating system
To alleviate the computational burden of previous virtual network embedding (VNE) approaches when the resource network scales up significantly, we propose an efficient node ranking strategy that considers both global and local topological characteristics of the substrate network in mapping virtual nodes to physical nodes. This method ranks the substrate network nodes in two stages. First, all nodes are ranked globally with respect to the stationary distribution of the entire network. Then, a connected subset of the ranked substrate nodes, forming the H ‐admissible embedding subgraph, is extracted. Finally, the subgraph nodes are ranked according to a local node ranking vector derived from a random‐walking scheme. The local rank vector is resolved using discrete Green's function satisfying the Dirichelet boundary condition. The more accurate association of node demands and resources that our proposed method provides leads to both better acceptance ratio and lower computational overhead. These claims have been justified via theoretical and algorithmic presentation of our scheme and offer experimental results obtained through simulation, to confirm its execution efficiency and solution quality compared with a couple of previous VNE proposals.