博弈论组合赋权的虚拟网络映射算法

Virtual Network Embedding Algorithm Based on Game Theory Combination Weighting

针对当前节点多指标排序的虚拟网络映射算法中,指标权重选取较为片面的问题,本文提出一种博弈论组合赋权的虚拟网络映射算法.首先提取网络节点特征指标,组成节点特征指标向量并构建决策矩阵,然后利用博弈论组合赋权模型对熵值法和层次分析法获取的节点指标权重向量进行均衡处理,得到最优权重向量,最后将最优权重向量与特征指标向量的内积作为节点排序的依据.该方法通过将主观赋权法与客观赋权法结合,实现了对节点指标权重向量的优化.仿真结果表明,算法能够适应环境变化得到更为合理的权重向量,提高了虚拟网络映射成功率和收益开销比.

As the index weight determining of multi-index ranking in the virtual network embedding algorithm is one-sided,a virtual network embedding algorithm based on game theory combination weighting is proposed.Firstly,the feature indicators of the nodes in network are extracted to form the node feature index vector and construct the decision matrix.Then,the game theory combination weighting model is used to equalize the node index weight vector that obtained by the entropy method and the analytic hierarchy process method.Finally,the inner product of the optimal weighted vector and the feature index weight vector are selected as the basis for node ranking.The subjective weighting method is combined with the objective weighting method to realize the optimal selection of the node index weight vector.Simulation results show that the algorithm can obtain more reasonable weight vectors according to environmental changes,which improves the acceptance ratio and the revenue to cost ratio.