基于可重构技术的网络节点节能问题关键技术研究
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摘要
互联网已经成为支撑现代社会经济发展、社会进步和科技创新的最重要的基础设施之一。随着互联网的日益普及,互联网在满足人们对网络的规模、功能和性能等方面需求的同时也逐渐暴露出一些问题。能耗方面,信息和通信技术行业作为全球增长最快的行业之一,其碳排放也随着行业的增长而不断增长,目前信息和通信技术领域的碳排放占全球的2%,这一比例将在2020年翻一番。2008年网络基础设施,包括路由器、服务器、交换机、冷却设施等设备共消耗8680亿度电,占全球总耗电量的5.3%。按照目前的增长趋势,到2025年,IT行业的平均能耗将达到2006年的5倍,网络领域更会达到13倍。能耗问题已成为信息和通信技术持续发展的重大障碍。国家863计划信息技术领域重大专项“新一代高可信网络”提出了“可重构柔性网络”的思想,致力于建设能够承载新型业务、提供可靠服务保证、用户规模可规划、网络资源可管理、节点服务能力可重构、绿色节能的下一代网络与业务国家试验床。针对绿色网络对网络节点节能的需求,本文依托可重构柔性网络的研究工作,研究网络节点的绿色节能技术。
本文从节点设备能耗跟随业务负载变化的思想出发,将节点能耗调整抽象为资源分配和资源调整的物理本质问题,研究基于可重构技术的网络节点能耗调整机制。首先研究基于构件运算的系统可重构理论；其次研究构件模型和构件能耗感知模型；再次研究基于构件重构的能耗细粒度调整方法；最后设计一种网络节点的低能耗转发架构。具体而言,本文主要研究成果如下：
●对构件重构的基本理论进行研究,定义了构件和重构操作的相关概念,提出了可重构系统的代数模型。针对可重构系统在形式化描述和重构建模方面的不足,用代数学方法对可重构构件,构件组合,可重构系统的属性和行为特征进行抽象,把构件组合定义成构件的“运算”实现,结合进程代数中算子的概念,定义了多种构件组合运算,建立了可重构系统的代数模型。在代数模型基础上,提出了重构建模和重构范式,为使用可重构技术实现能耗调整奠定了理论基础。
●针对构件的能耗感知问题进行研究,提出了内嵌能耗感知机制的构件模型。构件模型使用构件代理完成决策和重构部署,利用代理接口完成构件间的交互。在构件组装层面引入具有感知功能的容器隔离底层操作系统的影响,构件模型遵循重构范式实现构件连接关系的重构。构件模型为构件提供了运行环境,为重构操作提供了支撑。分析构件的能耗产生原因,根据构件开发过程和运行环境的特点定义了3个能耗特征量,提出了一种利用BP神经网络估算构件能耗的模型。能耗模型对3个能耗特征量进行度量,使用BP神经网络拟合出构件特征量与构件能耗的非线性函数关系,并通过实验验证了能耗感知模型的有效性。内嵌能耗感知机制的构件模型支持了构件重构并提供了能耗调整对象。
●针对时延敏感业务的能耗调整问题,提出了截止时间约束下的频率调节算法。首先分析了业务时延特性,结合可重构柔性网络思想提出了一种业务时延特性区分方法。根据时延敏感业务对节点服务性能的要求,提出了一种以构件运行截止时间为约束的频率调节算法。算法使用频率调节点密度在构件组内部快速选择频率调节点,通过插入频率调节代码降低构件能耗。最后使用Zebra容器原型和Wattch功耗仿真软件进行了仿真实验,实验结果表明,频率调节算法可以节省构件组20%-40%的能耗,可使构件组能耗跟随业务负载发生变化,实现设备能耗的细粒度调整。
●针对非时延敏感业务的能耗调整问题,提出了基于构件重构的能耗细粒度调整方法。为解决能耗调整时机的决策问题,提出了一种基于业务流特征分析的多时间尺度重构决策算法。该算法首先对到达业务流的突发水平进行分析选择合适的流模型,然后针对选定的流模型提取流特征进行能耗调整时机决策。仿真结果表明该算法可以准确选择流模型,可以提高能耗调整的成功率和准确率并能降低能耗调整对业务的影响。其次,在对构件化路由器低能耗模型分析的基础上,提出了基于构件重构的能耗细粒度调整方法。该方法使用布尔二次指数平滑法预测网络负载变化；使用遗传算法并行搜索构件配置空间,能够快速搜索出低能耗构件配置方案。使用真实网络流量进行实验,结果表明该方法能够根据负载的动态变化进行构件重构,能够使路由器能耗跟随业务负载进行变化,与传统算法相比可以节省60%的算法运行时间,降低构件组25%能耗,实现了设备能耗的细粒度调整。
●针对网络节点能耗调整机制的部署问题,基于交换中转发的思想设计了一种低能耗转发架构。该架构通过模糊转发流水交换减少了路由器转发和交换阶段的存储需求和访存次数。该机制复用多个低速节点构成多级流水线结构,可降低报文IP查表和交换的硬件实现复杂度。通过重构规模化执行部件间的连接拓扑,可以部署论文提出的能耗调整机制。建立了交换中转发机制的能耗模型,仿真结果表明该机制可将路由查表中的存储开销降低为传统先转发后交换机制的50%,并且可节省查表过程中12.5%的能耗。
本文的研究成果对准确把握构件可重构系统的宏观特征,实现构件能耗感知,部署能耗细粒度调整机制具有重要的应用价值,将直接为基于可重构技术实现能耗跟随负载变化和绿色网络能耗管理问题的解决提供研究思路和理论依据。
The internet has been one of important infrastructure to support Modern social and economic development, social progress and scientific and technological innovation. The Internet to meet people on the network size, functionality and performance needs, while also gradually revealed some problems. In energy consumption, information and communication technology industry as one of the fastest growing industries worldwide, Carbon emissions are also growing with the growth of the industry. The carbon emissions of information and communication technology accounted for2%of the world, which will be double in2020. Network infrastructure, including routers, servers, switches, cooling facilities and other equipment consume868billion kWh of electricity in2008, Accounting for5.3%of the world's total electricity consumption. With the current growth trends, in2025, The average energy consumption of the IT industry will reach five times that of2006, network areas will reach13times. Energy consumption has become a major obstacle to sustainable development in information and communication technology. National863Program IT major projects in the field of "A new generation of high-trusted network" proposed the reconfigurable flexible network idea. Committed to building capable of carrying a new business, provide a reliable service support to QoS, user scale planning, network resources can be managed, node service capabilities can reconfigure, building a green next-generation networks and services national test bed. On the demand of Green Network, this article relies on research of reconfigurable flexible network, studying the energy-saving technologies of the network nodes.
In this paper, we proposed an idea of node device energy consumption following the traffic load changes. Adjusting node energy consumption can be abstract to the physical nature of the resource allocation and resource adjustment. First, study reconfigurable theory based component computing system, second, study the energy consumption of the component perceptual model. Third, research a fine-grained adjustment method component-based reconstruction of the energy consumption. Last, design a low power scheme for the network nodes forwarding. Specifically, the main findings of this article are as follows:
This paper focuses on the lacks at methodology of describing formal model and reconfigurable attributes of the reconfigurable system, abstracts and describes the attributes and the behaviors of reconfigurable system, component combination and reconfigurable method by algebraic method. By understanding the component combination an operation, that is a new idea, and extending the calculus in process algebraic, some component combination operators are defined and then a formal algebraic model of reconfigurable system is proposed. Based this model some reconfigurable attributes are analyzed and a few reconfigurable nomal formats is proposed. All above viewpoints construct theoretical footstone for designing reconfigurable system.
This paper focuses on the energy-aware problem of components, starts at a software component architecture level, considers the functional relation between software component characteristic quantities and software energy as nonlinear (linear functional relation can be considered as a special nonlinear functional relation). Next, the paper presents an energy model at architecture level by using BP neural network. The energy model measures three software characteristic quantities at architecture level and uses BP neural network to fit the functional relation between software characteristic quantities and software energy. Experimental results show that this model is effective. Based on the energy aware model, energy aware component model is proposed. In this model, such as energy aware, decision, and execution are into components, and then supports their dynamic configuration with the reconfigure technology. Based on principles of the Separation of Concerns and the Dynamic Software Architecture (DSA) technology, the component model can help components running and reconfiguring.
For the delay-sensitive traffic, paper introduce the frequency scaling consistency and the algorithm assisted with could make dynamic frequency scaling by automatically inserting dynamic frequency scaling source code in presented. The algorithm has been realized in Zebra container prototype and Wattch emulator software. The results show that we can save20%-40%energy consumption of components. The meticulous-grained device energy scaling is implemented to validate that the components energy can changed with application load variety.
In order to solve the energy saving problem of no-delay-sensitive traffic, a multiscale reconfigure decision algorithm is proposed. The effective model of self-similarity or multiracial traffic was obtained using the Hurst index; the effective envelope is obtained using the effective bandwidth and effective envelope theorem. Then, traffic parameters are obtained using network calculus to perform reconfigures decision. The simulations prove that the traffic model can be selected accurately; the rate of success and accurate of reconfigure are improved; the effect to traffic delay is reduced. This paper proposes an energy meticulous-grained scaling algorithm to deal with the routers'energy problem, which is based on the idea that components energy can changed with application load variety. It first predicts the future workloads of the applications with Brown's quadratic exponential smoothing method to make reconfiguration catch up with loads. Next, it adopts a genetic algorithm to parallel find the optimal reconfiguration policy. The real network traffic is used to check the algorithm. Experimental results demonstrate the approach can adapt the router's energy according to the change of network traffic, save the algorithm computing time60%and greatly reduce the energy consumption25%.
We focus on the low-energy architecture designing problem of reconfigurable flexible network forwarding plane. In this paper, we consider building a FIS mechanism based forwarding in switching idea. The memory requiring and accessing reduced by blurredly forwarding and piping switching. The multilevel line framework in FIS is made by many slow processing units. It can obtain higher performance and lookup speed through cosmically running. Simultaneously, it can reduce the complexity of hardware implementation. Energy model of FIS and FBS is established. Experiments using real-life routing tables demonstrate that our FIS solution can reduce the power of routing lookup12.5%than FBS clearly.
The conclusions of this thesis offer a fine-grained adjustment method component-based reconstruction of the energy consumption which contains the energy resource allocation and resource adjustment, which is great valuable to accurately grasp the macro features of component reconfigurable system. And it can provide theoretical foundation and research model directly for the research on the green network based on the idea of node device energy consumption following the traffic load changes.
本文从节点设备能耗跟随业务负载变化的思想出发,将节点能耗调整抽象为资源分配和资源调整的物理本质问题,研究基于可重构技术的网络节点能耗调整机制。首先研究基于构件运算的系统可重构理论；其次研究构件模型和构件能耗感知模型；再次研究基于构件重构的能耗细粒度调整方法；最后设计一种网络节点的低能耗转发架构。具体而言,本文主要研究成果如下：
●对构件重构的基本理论进行研究,定义了构件和重构操作的相关概念,提出了可重构系统的代数模型。针对可重构系统在形式化描述和重构建模方面的不足,用代数学方法对可重构构件,构件组合,可重构系统的属性和行为特征进行抽象,把构件组合定义成构件的“运算”实现,结合进程代数中算子的概念,定义了多种构件组合运算,建立了可重构系统的代数模型。在代数模型基础上,提出了重构建模和重构范式,为使用可重构技术实现能耗调整奠定了理论基础。
●针对构件的能耗感知问题进行研究,提出了内嵌能耗感知机制的构件模型。构件模型使用构件代理完成决策和重构部署,利用代理接口完成构件间的交互。在构件组装层面引入具有感知功能的容器隔离底层操作系统的影响,构件模型遵循重构范式实现构件连接关系的重构。构件模型为构件提供了运行环境,为重构操作提供了支撑。分析构件的能耗产生原因,根据构件开发过程和运行环境的特点定义了3个能耗特征量,提出了一种利用BP神经网络估算构件能耗的模型。能耗模型对3个能耗特征量进行度量,使用BP神经网络拟合出构件特征量与构件能耗的非线性函数关系,并通过实验验证了能耗感知模型的有效性。内嵌能耗感知机制的构件模型支持了构件重构并提供了能耗调整对象。
●针对时延敏感业务的能耗调整问题,提出了截止时间约束下的频率调节算法。首先分析了业务时延特性,结合可重构柔性网络思想提出了一种业务时延特性区分方法。根据时延敏感业务对节点服务性能的要求,提出了一种以构件运行截止时间为约束的频率调节算法。算法使用频率调节点密度在构件组内部快速选择频率调节点,通过插入频率调节代码降低构件能耗。最后使用Zebra容器原型和Wattch功耗仿真软件进行了仿真实验,实验结果表明,频率调节算法可以节省构件组20%-40%的能耗,可使构件组能耗跟随业务负载发生变化,实现设备能耗的细粒度调整。
●针对非时延敏感业务的能耗调整问题,提出了基于构件重构的能耗细粒度调整方法。为解决能耗调整时机的决策问题,提出了一种基于业务流特征分析的多时间尺度重构决策算法。该算法首先对到达业务流的突发水平进行分析选择合适的流模型,然后针对选定的流模型提取流特征进行能耗调整时机决策。仿真结果表明该算法可以准确选择流模型,可以提高能耗调整的成功率和准确率并能降低能耗调整对业务的影响。其次,在对构件化路由器低能耗模型分析的基础上,提出了基于构件重构的能耗细粒度调整方法。该方法使用布尔二次指数平滑法预测网络负载变化；使用遗传算法并行搜索构件配置空间,能够快速搜索出低能耗构件配置方案。使用真实网络流量进行实验,结果表明该方法能够根据负载的动态变化进行构件重构,能够使路由器能耗跟随业务负载进行变化,与传统算法相比可以节省60%的算法运行时间,降低构件组25%能耗,实现了设备能耗的细粒度调整。
●针对网络节点能耗调整机制的部署问题,基于交换中转发的思想设计了一种低能耗转发架构。该架构通过模糊转发流水交换减少了路由器转发和交换阶段的存储需求和访存次数。该机制复用多个低速节点构成多级流水线结构,可降低报文IP查表和交换的硬件实现复杂度。通过重构规模化执行部件间的连接拓扑,可以部署论文提出的能耗调整机制。建立了交换中转发机制的能耗模型,仿真结果表明该机制可将路由查表中的存储开销降低为传统先转发后交换机制的50%,并且可节省查表过程中12.5%的能耗。
本文的研究成果对准确把握构件可重构系统的宏观特征,实现构件能耗感知,部署能耗细粒度调整机制具有重要的应用价值,将直接为基于可重构技术实现能耗跟随负载变化和绿色网络能耗管理问题的解决提供研究思路和理论依据。
The internet has been one of important infrastructure to support Modern social and economic development, social progress and scientific and technological innovation. The Internet to meet people on the network size, functionality and performance needs, while also gradually revealed some problems. In energy consumption, information and communication technology industry as one of the fastest growing industries worldwide, Carbon emissions are also growing with the growth of the industry. The carbon emissions of information and communication technology accounted for2%of the world, which will be double in2020. Network infrastructure, including routers, servers, switches, cooling facilities and other equipment consume868billion kWh of electricity in2008, Accounting for5.3%of the world's total electricity consumption. With the current growth trends, in2025, The average energy consumption of the IT industry will reach five times that of2006, network areas will reach13times. Energy consumption has become a major obstacle to sustainable development in information and communication technology. National863Program IT major projects in the field of "A new generation of high-trusted network" proposed the reconfigurable flexible network idea. Committed to building capable of carrying a new business, provide a reliable service support to QoS, user scale planning, network resources can be managed, node service capabilities can reconfigure, building a green next-generation networks and services national test bed. On the demand of Green Network, this article relies on research of reconfigurable flexible network, studying the energy-saving technologies of the network nodes.
In this paper, we proposed an idea of node device energy consumption following the traffic load changes. Adjusting node energy consumption can be abstract to the physical nature of the resource allocation and resource adjustment. First, study reconfigurable theory based component computing system, second, study the energy consumption of the component perceptual model. Third, research a fine-grained adjustment method component-based reconstruction of the energy consumption. Last, design a low power scheme for the network nodes forwarding. Specifically, the main findings of this article are as follows:
This paper focuses on the lacks at methodology of describing formal model and reconfigurable attributes of the reconfigurable system, abstracts and describes the attributes and the behaviors of reconfigurable system, component combination and reconfigurable method by algebraic method. By understanding the component combination an operation, that is a new idea, and extending the calculus in process algebraic, some component combination operators are defined and then a formal algebraic model of reconfigurable system is proposed. Based this model some reconfigurable attributes are analyzed and a few reconfigurable nomal formats is proposed. All above viewpoints construct theoretical footstone for designing reconfigurable system.
This paper focuses on the energy-aware problem of components, starts at a software component architecture level, considers the functional relation between software component characteristic quantities and software energy as nonlinear (linear functional relation can be considered as a special nonlinear functional relation). Next, the paper presents an energy model at architecture level by using BP neural network. The energy model measures three software characteristic quantities at architecture level and uses BP neural network to fit the functional relation between software characteristic quantities and software energy. Experimental results show that this model is effective. Based on the energy aware model, energy aware component model is proposed. In this model, such as energy aware, decision, and execution are into components, and then supports their dynamic configuration with the reconfigure technology. Based on principles of the Separation of Concerns and the Dynamic Software Architecture (DSA) technology, the component model can help components running and reconfiguring.
For the delay-sensitive traffic, paper introduce the frequency scaling consistency and the algorithm assisted with could make dynamic frequency scaling by automatically inserting dynamic frequency scaling source code in presented. The algorithm has been realized in Zebra container prototype and Wattch emulator software. The results show that we can save20%-40%energy consumption of components. The meticulous-grained device energy scaling is implemented to validate that the components energy can changed with application load variety.
In order to solve the energy saving problem of no-delay-sensitive traffic, a multiscale reconfigure decision algorithm is proposed. The effective model of self-similarity or multiracial traffic was obtained using the Hurst index; the effective envelope is obtained using the effective bandwidth and effective envelope theorem. Then, traffic parameters are obtained using network calculus to perform reconfigures decision. The simulations prove that the traffic model can be selected accurately; the rate of success and accurate of reconfigure are improved; the effect to traffic delay is reduced. This paper proposes an energy meticulous-grained scaling algorithm to deal with the routers'energy problem, which is based on the idea that components energy can changed with application load variety. It first predicts the future workloads of the applications with Brown's quadratic exponential smoothing method to make reconfiguration catch up with loads. Next, it adopts a genetic algorithm to parallel find the optimal reconfiguration policy. The real network traffic is used to check the algorithm. Experimental results demonstrate the approach can adapt the router's energy according to the change of network traffic, save the algorithm computing time60%and greatly reduce the energy consumption25%.
We focus on the low-energy architecture designing problem of reconfigurable flexible network forwarding plane. In this paper, we consider building a FIS mechanism based forwarding in switching idea. The memory requiring and accessing reduced by blurredly forwarding and piping switching. The multilevel line framework in FIS is made by many slow processing units. It can obtain higher performance and lookup speed through cosmically running. Simultaneously, it can reduce the complexity of hardware implementation. Energy model of FIS and FBS is established. Experiments using real-life routing tables demonstrate that our FIS solution can reduce the power of routing lookup12.5%than FBS clearly.
The conclusions of this thesis offer a fine-grained adjustment method component-based reconstruction of the energy consumption which contains the energy resource allocation and resource adjustment, which is great valuable to accurately grasp the macro features of component reconfigurable system. And it can provide theoretical foundation and research model directly for the research on the green network based on the idea of node device energy consumption following the traffic load changes.
引文
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