面向核心网的多层网络能耗优化方法

发布时间：2018-02-24 23:30

本文关键词： 绿色网络能耗优化核心网多层网络 IPover TDM over WDM 绿色计算　出处：《计算机学报》2013年07期 　论文类型：期刊论文

【摘要】：随着网络规模和流量的迅速增长,Internet的能耗问题变得日益严重.文中研究IP(Internet Protocol)over TDM over WDM核心网的能耗问题,首先对多层网络的节能机制进行了分析,在此基础上,提出了一种多层网络能耗优化的ITO模型,充分考虑多层网络的体系结构和网络设备的模块化特性,协同使用网络业务流控制和网络资源配置与管理的方法,实现业务流在多个网络层合理的分配和路由以及网络设备的多粒度模块睡眠,以达到降低网络能耗的目的.实验结果表明,ITO模型能有效降低网络的能耗,在网络业务量较低时,可将网络功耗降到业务高峰期时的24%～38%.此外,该文还通过实验探讨了业务的疏导和旁通、不同的网络层组合、网络设备的动态功耗以及网络设备的模块化结构对网络能耗优化的影响,为构建节能高效的绿色网络提供了参考.
[Abstract]:With the rapid growth of network size and traffic, the problem of energy consumption in IP(Internet Protocol)over TDM over WDM network becomes more and more serious. In this paper, the energy consumption of IP(Internet Protocol)over TDM over WDM network is studied. Firstly, the energy saving mechanism of multi-layer network is analyzed. In this paper, a ITO model of multi-layer network energy consumption optimization is proposed, which takes into account the architecture of multi-layer network and the modularization of network equipment, and uses the method of network traffic control and network resource configuration and management. In order to reduce the network energy consumption, the ITO model can effectively reduce the network energy consumption, when the network traffic is low, the network traffic can be allocated and routed reasonably in multiple network layers, and the multi-granularity module sleep of the network equipment can be achieved, the experimental results show that the ITO model can effectively reduce the network energy consumption, when the network traffic is low, The power consumption of the network can be reduced to 24 / 38 during the peak period of service. In addition, the paper also discusses the traffic diversion and bypass through experiments, different network layer combinations, The influence of dynamic power consumption of network equipment and modularization structure of network equipment on the optimization of network energy consumption provides a reference for the construction of energy saving and efficient green network.
【作者单位】：四川大学计算机学院;成都信息工程学院控制工程学院;
【基金】：国家自然科学基金(61272104,61073045) 四川省杰出青年科技基金(2010JQ0011) 中国科学院计算技术研究所计算机体系结构国家重点实验室开放课题(ICT-ARCH201003)资助~~
【分类号】：TP393.02

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