软件学报
軟件學報
연건학보
JOURNAL OF SOFTWARE
2014年
7期
1416-1431
,共16页
陈晓华%李春芝%陈良育%曾振柄
陳曉華%李春芝%陳良育%曾振柄
진효화%리춘지%진량육%증진병
虚拟网络映射%主动休眠%高效节能%资源整合
虛擬網絡映射%主動休眠%高效節能%資源整閤
허의망락영사%주동휴면%고효절능%자원정합
virtual network embeding%actively hibernate%energy efficient%resource consolidation
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。
網絡虛擬化,使得智能能量感知網絡部署成為可能。由于噹前網絡為高峰負荷而設計,導緻資源利用率不足及能量浪費。而網絡設備能量消耗對于流量負載不敏感,資源整閤成為有效節能技術。根據虛擬網絡映射特點及底層網絡能耗,提齣虛擬網絡映射節能多目標決策模型;由于該模型是混閤整數規劃模型,求解時間複雜度高,通過分析虛擬網絡映射動態特徵,構造虛擬網絡映射字典庫,提齣底層網絡資源利用率的訓練方法以及主動休眠底層節點和鏈路算法,把虛擬網絡映射在一箇較小的節點和鏈路集閤中,提高休眠節點和鏈路數量,實現高效節能虛擬網絡映射。繫統倣真結果驗證瞭主動休眠方法能夠提高底層節點和鏈路休眠數量,顯著減少繫統能耗。
망락허의화,사득지능능량감지망락부서성위가능。유우당전망락위고봉부하이설계,도치자원이용솔불족급능량낭비。이망락설비능량소모대우류량부재불민감,자원정합성위유효절능기술。근거허의망락영사특점급저층망락능모,제출허의망락영사절능다목표결책모형;유우해모형시혼합정수규화모형,구해시간복잡도고,통과분석허의망락영사동태특정,구조허의망락영사자전고,제출저층망락자원이용솔적훈련방법이급주동휴면저층절점화련로산법,파허의망락영사재일개교소적절점화련로집합중,제고휴면절점화련로수량,실현고효절능허의망락영사。계통방진결과험증료주동휴면방법능구제고저층절점화련로휴면수량,현저감소계통능모。
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.