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虚拟网络映射是网络虚拟化研究的关键内容,利用传统遗传算法解决虚拟网络映射问题,由于遗传算法本身的缺点使得问题容易过早进入局部最优解,且收敛速度慢.在基本遗传算法中加入改进的单纯形算法,以最大化In Ps的收益为目标,建立混合整数线性规划(MILP)模型,提出VNE-M-GA的虚拟网络映射算法.该算法利用单纯形法预估寻优方向,遗传算法和单纯形法迭代优化映射方案,尽可能的避免局部最优.实验结果表明该方法解决虚拟网络映射问题,与现有算法实验结果相比,一定程度改进了早熟收敛问题,提高了In Ps总收益与虚拟网络请求接受率.
Virtual network mapping is the key content of network virtualization research, and the traditional genetic algorithm is used to solve the problem of virtual network mapping. Because of the shortcomings of genetic algorithm itself, the problem easily gets into the local optimal solution prematurely and the convergence speed is slow .In the basic genetic algorithm In order to maximize the profit of In Ps, a modified mixed integer linear programming (MILP) model is proposed and the virtual network mapping algorithm of VNE-M-GA is proposed.The algorithm uses the simplex method to predict the direction of optimization, Genetic algorithm and simplex iterative optimization mapping scheme, as far as possible to avoid local optima.Experimental results show that the method to solve the virtual network mapping problem, compared with the existing algorithm experimental results, to some extent improve the premature convergence problem, improve the In Ps total revenue and virtual network request acceptance rate.