网络虚拟化，使得智能能量感知网络部署成为可能。由于当前网络为高峰负荷而设计，导致资源利用率不足及能量浪费。而网络设备能量消耗对于流量负载不敏感，资源整合成为有效节能技术。根据虚拟网络映射特点及底层网络能耗，提出虚拟网络映射节能多目标决策模型；由于该模型是混合整数规划模型，求解时间复杂度高，通过分析虚拟网络映射动态特征，构造虚拟网络映射字典库，提出底层网络资源利用率的训练方法以及主动休眠底层节点和链路算法，把虚拟网络映射在一个较小的节点和链路集合中，提高休眠节点和链路数量，实现高效节能虚拟网络映射。系统仿真结果验证了主动休眠方法能够提高底层节点和链路休眠数量，显著减少系统能耗。%Network virtualization will be an enabler for intelligent energy-aware network deployment. Current networks are designed for peak loads, resulting in inadequate resource utilization and energy consumption waste. Due to current power consumption insensitiveness of network equipment to traffic load, resource consolidation becomes an effective energy-saving technology. Based on the virtual network mapping characteristics and the substrate network energy consumption, this paper presents a multi-objective decision-making model that is also a mixed integer programming model for energy efficient virtual network embedding. To address high time complexity in solving the mixed integer programming model, the paper analyzes the dynamic characteristics of the virtual network mapping, constructs virtual network mapping dictionary database and proposes a method for training substrate network resource utilization, as well as an algorithm which actively hibernates the substrate nodes and links. By this method, the virtual network can be embedded in a smaller set of substrate nodes and links, which helps to increase the number of hibernating substrate nodes and links, and achieve energy-effective virtual network mapping. Simulation results demonstrate the proposed method can effectively improve the number of hibernating nodes and links of substrate network, and significantly reduce energy consumption of substrate network.
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