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Journal of Software:2017.28(7):1790-1814

高效节能虚拟网络映射多反馈控制模型及算法
陈晓华,李春芝,陈良育,曾振柄,蒋云良
(湖州师范学院 信息工程学院, 浙江 湖州 313000;华东师范大学 计算机科学与软件工程学院, 上海 200062;上海大学 数学系, 上海 200444)
Multiple Feedback Control Model and Algorithm for Energy Efficient Virtual Network Embedding
CHEN Xiao-Hua,LI Chun-Zhi,CHEN Liang-Yu,ZENG Zhen-Bing,JIANG Yun-Liang
(School of Information Engineering, Huzhou University, Huzhou 313000, China;School of Computer Science and Software Engineering, East China Normal University, Shanghai 200062, China;Department of Mathematics, Shanghai University, Shanghai 200444, China)
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Received:June 30, 2014    Revised:March 07, 2016
> 中文摘要: 网络虚拟化使得智能能耗感知网络部署成为可能.由于虚拟网络请求到来以及退出等动态性,引起底层网络资源分配以及回收,会对底层网络激活资源数量与集合范围产生影响;虚拟网络映射不仅决定了当前激活的底层网络资源数量与集合大小,而且作用于后续的虚拟网络映射.利用自动控制原理的反馈控制理论,研究不同虚拟网络映射之间的关系以及当前虚拟网络映射对激活底层网络资源集合产生的影响,并提出一种新的高效节能虚拟网络映射多反馈控制模型及算法.以控制底层网络休眠链路数量作为主反馈,消除主动休眠的底层网络链路数量与被动休眠的链路数量的偏差,抑制虚拟网络映射动态特征对求解最小底层网络激活资源集合的干扰;并以节点和链路映射为局部反馈,由大到小逐步调整主动休眠底层链路数量,快速地找到适合当前虚拟网络请求的最小底层网络资源集合.多反馈控制模型能够把虚拟网络映射在一个较小的节点和链路集合中,从而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在非饱和状态下虚拟网络映射多反馈控制算法能够提高底层节点和链路休眠数量,显著减少系统能耗;且在负载周期性动态变化的饱和状态下,提高了虚拟网络接收率以及系统收益.
Abstract:Network virtualization will be an enabler for intelligent energy-aware network deployment. Since virtual network requests arrive dynamically and stay in the network for an arbitrary period of time before departing, substrate resources are allocated and recycled dynamically, which influence the set range and the number of the active resources. Current network mapping not only determines the setrange and the number of the active resources, but also influences the subsequent virtual network mapping. To address the problems, this paper uses the feedback control theory to investigate the relationship among virtual network embeddings, and the impact of current mapping on active resources of substrate network. A novel multi-feedback control model and an algorithm are proposed for energy-efficient virtual network embedding. In this model, a main feedback control is placed to manage the number of hibernating links of substrate network, eliminating the deviations of the number of the active hibernating links and the passive hibernating links. This method helps eliminate the interferences on the minimum set of active substrate resources. In addition, a local feedback control for mapping virtual nodes and links is designed to reduce the number of active hibernating substrate links. As a result, the minimum set of substrate resource for one virtual network can be searched. Using this model, a smaller set of substrate nodes and links can be found for virtual network requests, which increase the number of passive hibernating nodes and links and decreases the energy consumption of substrate network. Simulation results demonstrate the proposed algorithm to be effective. The proposed model and the corresponding method can cut down the number of hibernating nodes and links of substrate network, and significantly reduce the energy consumption of substrate network in non-saturated state. Moreover, they can improve acceptance and revenue of virtual network in saturated environment with cyclical fluctuations in traffic.
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基金项目:浙江省自然科学基金(LY17F020007);国家自然科学基金(61501184,61370173,61503136);湖州市科技计划(2014GZB02) 浙江省自然科学基金(LY17F020007);国家自然科学基金(61501184,61370173,61503136);湖州市科技计划(2014GZB02)
Foundation items:Natural Science Foundation of Zhejiang Province, China (LY17F020007); National Natural Science Foundation of China (61501184, 61370173, 61503136); Science and Technology Planning Project of Huzhou City (2014GZB02)
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陈晓华,李春芝,陈良育,曾振柄,蒋云良.高效节能虚拟网络映射多反馈控制模型及算法.软件学报,2017,28(7):1790-1814

CHEN Xiao-Hua,LI Chun-Zhi,CHEN Liang-Yu,ZENG Zhen-Bing,JIANG Yun-Liang.Multiple Feedback Control Model and Algorithm for Energy Efficient Virtual Network Embedding.Journal of Software,2017,28(7):1790-1814