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论文类型：期刊论文

发表时间：2015-02-15

发表刊物：COMPUTER COMMUNICATIONS

收录刊物：SCIE、EI

卷号：57

页面范围：25-36

ISSN号：0140-3664

关键字：Probabilistic inference; SLO assurance; Virtual network; Virtual network reconfiguration

摘要：Network virtualization enables multiple service providers to share the same physical infrastructure, and allows physical substrate network (SN) resources to be used in the form of a virtual network (VN). However, there are many obstacles to the application of this technology. One of the more challenging is the reconfiguration of SN-embedded VNs to adapt to varying demands. To address this problem, we propose a service level objective (SLO)-sensitive VN reconfiguration (VNR) method. A Bayesian network learning and probabilistic reasoning-based approach is proposed to automatically localise reconfiguration points and generate VN resource requests. To determine an optimal reconfiguration solution, we design a heuristic VNR algorithm with a virtual node and virtual link swapping strategy. We validate and evaluate this algorithm by conducting experiments in a high-fidelity emulation environment. Our results show that the proposed approach can effectively reconfigure a VN to adapt to a changed SLO. A comparison shows that our reconfiguration algorithm outperforms existing solutions. (C) 2014 Elsevier B.V. All rights reserved.