绿色网络理论与技术研究

互联网的飞速发展,也使网络能耗急剧增长.但目前网络设备能效低下,未实现能耗比例计算的理念.而网络却为峰值负载而设计,在众多时间处于低负载,存在巨大的节能契机.首先介绍网络设备的能耗模型,继而从两方面阐述网络能耗优化的理论与技术:一方面,在假设网络总流量无法改变的前提下,为网络设备增加能源和性能状态,并优化本地控制策略,从而使单个网络设备实现能耗比例计算,或者在不提高现有网络设备能效的前提下,通过网络范围的协同和流量工程,使网络整体实现能耗比例计算的理念;另一方面,为网络提供缓存能力可以降低或缓解网络流量,从而减少网络的传输能耗或缓解其增长速度,智能的缓存部署、内容存储和请求路由能够进一步优化网络的能耗.在上述基础上,比较了各种技术的优劣,并分析了未来的研究方向.     

无线传感器网络跨层自适应唤醒算法研究

时钟同步与能耗有效性是无线传感器网络多跳传输关键问题.提出一种自适应唤醒算法,在MAC层和网络层进行跨层优化,节点按需自适应唤醒,实现多跳网络的协同传输,能够有效降低系统能耗.该算法不需要节点间的周期性同步,减少了频繁的包交换带来的数据冲突与能量浪费,从而提高了网络可靠性和能耗效率,提高了基于IEEE802.15.4标准的多跳网络的节能效率.为了验证算法有效性,工作分别在NS-2仿真环境和实际应用场景下进行了仿真与测试验证,结果表明在传输可靠性和节能效率上均由较大提高.跨层自适应唤醒算法可进一步推广到大规模异构自组织网络中.     

基于多层虚拟拓扑节能的SDN数据中心网络流量调度算法

针对“富连接”数据中心网络在低负载时能源利用率较低的问题,提出一种节能的多层虚拟拓扑流量调度算法(EMV-SDN)。建立节能流量调度问题的整形线性规划(Integral Linear Programing,ILP)优化数学模型,使得在承载所有网络负载的前提下,网络能源消耗最小。提出节能的多层虚拟拓扑流量调度算法来求解数学优化模型,得到数据流的节能调度方案。通过休眠高层的虚拟拓扑和交换机端口实现节能,降低网络能源消耗。实验结果表明,在网络能耗和数据流平均完成时间等方面,EMV-SDN算法均优于ECMP(Equal-Cost Multi-Path Routing)以及Dijkstra最短路径算法。     

一种综合IP层和WDM层资源的光网络动态路由优化模型及其性能研究

在分层图模型的基础上,本文提出一种以最小化全网光路总代价为优化目标的IP over WDM光网络动态路由优化模型,设计了一种针对该模型的在线综合路由算法——MCTLP（Minimizing the Cost of Total Lightpaths）,MCTLP通过综合考虑IP逻辑层带宽资源分配和WDM光物理层波长链路资源的占用以优化网络资源。与两种有代表性的IP over WDM光网络路由算法的性能仿真时比表明：MCTLP能够在IP逻辑层和WDM光物理层都使用较少的链路以承载IP业务流,接纳更多的IP业务连接请求,有效地降低网络阻塞率．     

快速自适应调频机制及其在NetFPGA上的实现

降低网络设备能耗已经成为当前研究的热点.文中,作者设计了一种能够实时适应流量变化的动态自适应频率调整方法FASS,它能根据处理模块的负载,实时地调整模块的工作频率,从而有效降低模块的能耗.同时,作者通过修改NetFPGA的参考路由器设计,将FASS添加到数据包处理模块中来验证FASS的性能.马尔可夫模型分析结果和实际实验的测试结果表明,在仅增加可容忍的延迟的情况下,FASS在多种不同的负载情况下,都能有效地降低模块功耗.另外,作者的工作说明FASS可以应用于实际的物理设备中以实现节能.     

网络能耗系统模型及能效算法

网络能耗问题是当前网络研究和发展的重要问题,影响着网络的设计、应用和发展.当前网络能效算法的研究大多从网络局部角度关注于网络某一(些)设施的能耗问题,缺乏从网络全局的角度研究网络整体能耗的算法和策略.文中从网络全局角度研究网络的能耗模型和算法问题.文中基于3种基本网络数据传递模式和3种基本网络能耗机制,构建了网络能耗系统优化模型,对其中5种关键系统模型给出了详细的描述.针对几个关键系统模型,文中给出了形式化描述并且提出了相应的优化的节能路由算法.文中给出的网络系统能耗优化模型有助于对于网络能耗的理解和分析,所提出的能耗优化的网络数据包路由算法可以从网络路由的角度有效降低网络能耗.     

一种速率自适应的能耗优化路由策略研究

降低网络系统能耗是当前计算机领域构建绿色网络迫切需要解决的关键问题.网络设备的传输服务速率自适应性为优化网络能耗和提高网络能效提供了有效的途径,文中提出一种基于速率自适应的全局性和分布式的能耗优化路由策略.该策略从网络全局路由的角度出发,根据网络系统的服务特征,将为数据提供传输服务的网络组件抽象为一个处理域.为求解处理域中速率自适应时的服务速率和工作状态平均转换次数,把处理域的服务过程视为可变服务速率的服务系统.然后以网络系统总能耗最小化为目标,并满足相关的路由和性能等约束条件,建立基于速率自适应的网络能耗优化路由模型,利用改进的蚁群算法对模型进行求解.在仿真实验中,将文中提出的能耗优化路由的分布式启发算法与相关文献的OSPF和GreenOSPF节能路由算法进行比较,给出算法在能耗和延时方面的对比结果.多种实验情况下的对比结果表明,文中提出的能耗优化路由策略能更有效地匹配速率自适应机制,具有较好的节能效果,从而达到优化和降低能耗的目的.     

异构网络中多模终端业务流分发技术研究

伴随着异构网络的迅猛发展,多模终端日益普及.当终端上有多种不同类型的会话业务流需要传输时,如何根据不同类型业务流的特点、不同网络的当前链路状况、通信费用、传输功耗等因素,在终端所接入的多个网络之间自动地、合理地分发业务流就成为一个非常重要的问题.文中提出了一套针对多模终端业务流分发问题的解决方案,包括支持业务流自动分发的多模终端框架结构及其包含的业务流分发算法.方案引入优先级的概念使得高等级的业务流在网络负载较重时具有使用网络的优先权,同时方案包含了一种权重自生成方法,为影响业务流分发决策的多个属性自动生成权重,减轻了用户负担,避免了由用户直接指定权重的困难.仿真实验的结果表明,文中方案能够根据当前各接入网络的链路状况、不同类型业务流的服务质量需求、传输功耗、通信成本等多个属性,自动为多模终端上运行的各条业务流选择合理的接入网络,同时方案在吞吐量、会话完成率等性能指标上也拥有显著改进.     

基于超宽带技术的无线传感器数据传输网络跨层优化研究

通过构建、求解MAC层、物理层、网络层跨层优化模型的方式,对超宽带无线传感器网络数据传输问题进行了初步研究.仿真实验结果表明,以构建、求解优化模型的方式解决无线传感器网络跨层设计问题是切实可行的,物理层信号功率控制、网络层路由对网络整体性能有着至关重要的影响.为超宽带无线传感器网络实际应用提供了必要的理论及实验依据,同时也为解决大规模超宽带传感器网络数据传输问题提供了解决思路.     

改进的遗传算法无线视频传感器网络协作路由技术研究

提出了适用于无线视频传感器网络的基于能量感知的跨层交互多路径协作路由技术.该技术首先采用了基于视频传感器节点感知距离的遗传优化算法,预测传输视频数据的能耗和剩余能量,结合无线信道质量和视频编码算法建立一种跨层协同的工作体系,优化节点传输视频数据的能耗、时延和带宽等因素;然后建立应用层、网络层和物理层跨层协同工作体系.仿真实验和数学分析表明,该技术不仅能够较好地满足视频传感器网络应用业务的多样性QoS数据传输性能需求,而且可以充分利用视频传感器网络受限的计算、存储能力和能量等资源.     

Stabilization of multiple independent linear systems with control networks

The problem of stabilizing multiple independent linear systems sharing one conmmon network cable is presented and solved. Both the quanfization and time sequencing are studied in the field of control over networks by providing the formulated stabilizing sufficient condition which illustrates the relationship between the system instability, quanfization and time sequencing, and the data rate is also presented in temps of the quanfization and time sequencing. A numerical example is given to illustrate the result.     

Efficient routing redundancy design over lossy networks

In this paper, a wireless networked control system is made robust with respect to packet losses by exploiting routing redundancy. Multiple copies of sensing and actuation data are sent via different routing paths, associated to possibly different delays. Similar to linear network coding, such data are recombined as a weighted linear combination. A MIMO output‐feedback architecture is considered. A methodology that takes into account both the network parameters and the plant dynamics is proposed to set up an optimization problem to design network weights to satisfy a robustness metric based on the notion of asymptotic mean‐square stability. Such metric induces either an objective or a constraint function that is nonlinear. For this reason, an efficient suboptimal design methodology is also proposed. Finally, the solutions are compared with the optimal choice from the communication designer point of view, which is based on the minimization of the quadratic error induced by the network on the actuation signal. The suboptimal methodology is shown, by means of a nontrivial example, to give results extremely close to the optimum with a strongly reduced computation time. It is also shown that the optimal choice from the communication design point of view, which neglects the plant dynamics, does not guarantee stochastic stability.     

Thresholds: On the Need for Frame Discarding in Cell-Switched Networks

This paper introduces a novel policing mechanism, called Packet Leaky Bucket in which all cells of a frame are marked with the same level of priority. Moreover, it discusses the need for having a frame discard mechanism in cell-switched networks when frame-oriented policing mechanisms are used.     

一种提高无线网络语音通话数量的方法

语音通话(Voice over IP)已经成为无线局域网中的一种重要的应用,并且近年来得到了越来越广泛的关注.分析了无线局域网所能支持的语音通话的最大数量,并在网络仿真器NS2上建立了IEEE 802.11语音通话的仿真模型根据仿真分析结果,提出一种自适应传输间隔接入控制方法,提高了IEEE 802.11无线局域网支持语音通话的数量.在自适应传输间隔接入控制方法中,基站(Base Station)通过监测网络冲突概率,自适应的改变网络中语音通话的传输间隔,使网络始终工作在非饱和状态.仿真实验结果表明,提出的白适应传输间隔接入控制方法不仅能够保证IEEE 802.11无线局域网中语音通话的质量,还可以增加网络所能支持语音通话的数量.     

Efficient Path Routing Over Road Networks in the Presence of Ad-Hoc Obstacles

Nowadays, the path routing over road networks has become increasingly important, yet challenging, in many real-world applications such as location-based services (LBS), logistics and supply chain management, transportation systems, map utilities, and so on. While many prior works aimed to find a path between a source and a destination with the smallest traveling distance/time, they do not take into account the quality constraints (e.g., obstacles) of the returned paths, such as uneven roads, roads under construction, and weather conditions on roads. Inspired by this, in this paper, we consider two types of ad-hoc obstacles, keyword-based and weather-based obstacles, on road networks, which can be used for modeling roads that the returned paths should not pass through. In the presence of such ad-hoc obstacles on roads, we formulate a path routing query over road networks with ad-hoc obstacles (PRAO), which retrieves paths from source to destination on road networks that do not pass ad-hoc keyword and weather obstacles and have the smallest traveling time. In order to efficiently answer PRAO queries, we design effective pruning methods and indexing mechanism to facilitate efficient PRAO query answering. Extensive experiments have demonstrated the efficiency and effectiveness of our approaches over real/synthetic data sets.     

基于ZigBee的智能环卫垃圾桶设计

在TI公司的CC2430芯片和ZigBee协议栈基础上,设计一种ZigBee技术的智能环卫垃圾桶。该原型由重量传感器、激光传感器、热红外感应器、语音芯片等组成。在电路设计方面,采用太阳能电池等绿色环保部件,使其更加符合绿色环保理念。城市环卫部门可通过ZigBee无线网络方便快捷的实时监控城市垃圾环卫信息,及时对垃圾进行清理,确保环境卫生,极大的方便了城市垃圾的管理。     

基于P2P的语言IP穿越网络地址转换和防火墙的统一模型

从P2P网络出发,提出了一种新的语言IP（Voice over IP,VoIP）穿越网络地址转换（Network Address Translation,NAT）和防火墙的统一模型。该模型利用分布式P2P网络的二层拓扑结构,通过最优路径建立算法（Optimal Path Establishment Algorithm,OPEA）以一种更有效的方式组织会话建立过程,使之能在各种情况下对NAT和防火墙的穿透问题提供最优解。与STUN等单一模型相比,具有更高的效率和健壮性。通过建立原型系统,在校园网环境中进行了模拟测试,证实了该模型的可行性以及提高服务质量的有效性。     

Adaptive playout scheduling algorithm tailored for real-time packet-based voice conversations over wireless ad-hoc networks

The effective provision of real-time, packet-based voice conversations over multi-hop wireless ad-hoc networks faces several stringent constraints not found in conventional packet-based networks. Indeed, MANETs (mobile ad-hoc networks) are characterized by mobility of all nodes, bandwidth-limited channel, unreliable wireless transmission medium, etc. This environment will surely induce a high delay variation and packet loss rate impairing dramatically the user experienced quality of conversational services such as VoIP. Indeed, such services require the reception of each media unit before its deadline to guarantee a synchronous playback process. This requirement is typically achieved by artificially delaying received packets inside a de-jitter buffer. To enhance the perceptual quality the buffering delay should be adjusted dynamically throughout the vocal conversation.In this work, we describe the design of a playout algorithm tailored for real-time, packet-based voice conversations delivered over multi-hop wireless ad-hoc networks. The designed playout algorithm, which is denoted MAPA (mobility aware playout algorithm), adjusts the playout delay according to node mobility, which characterizes mobile ad-hoc networks, and talk-spurt, which is an intrinsic feature of voice signals. The detection of mobility is done in service passively at the receiver using several metrics gathered at the application layer. The perceptual quality is estimated using an augmented assessment approach relying on the ITU-T E-Model paradigm while including the time varying impairments observed by users throughout a packet-based voice conversation. Simulation results show that the tailored playout algorithm significantly outperforms conventional playout algorithms, specifically over a MANET with a high degree of mobility.     

Signal-to-noise ratio fundamental limitations in the discrete-time domain

Fundamental limitations in feedback control are a well established area of research. In recent years it has been extended to the study of limitations imposed by the consideration of a communication channel in the control loop. Previous results characterised these limitations in terms of a minimal data transmission rate necessary for stabilisation. In this paper a signal-to-noise ratio (SNR) approach is used to obtain a tight condition for the linear time invariant output feedback stabilisation of a discrete-time, single-input-single-output (SISO) unstable, non-minimum phase (NMP) plant with arbitrary relative degree over an additive Gaussian coloured noise (ACGN) communication channel with memory. The obtained result gives a guideline in estimating the severity of the fundamental SNR limitation imposed by the plant unstable poles, NMP zeros and relative degree as well as the channel NMP zeros, bandwidth, and noise colouring. We then characterise the output feedback sensitivity function for the infimal SNR solution and follow up by quantifying the extra SNR imposed by suboptimal solutions (for example due to plant modelling errors).     

Learning-TCP: A stochastic approach for efficient update in TCP congestion window in ad hoc wireless networks

In this work, we attempt to improve the performance of TCP over ad hoc wireless networks (AWNs) by using a learning technique from the theory of learning automata. It is well-known that the use of TCP in its present form, for reliable transport over AWNs leads to unnecessary packet losses, thus limiting the achievable throughput. This is mainly due to the aggressive, reactive, and deterministic nature in updating its congestion window. As the AWNs are highly bandwidth constrained, the behavior of TCP leads to high contentions among the packets of the flow, thus causing a high amount of packet loss. This further leads to high power consumption at mobile nodes as the lost packets are recovered via several retransmissions at both TCP and MAC layers. Hence, our proposal, here after called as Learning-TCP, focuses on updating the congestion window in an efficient manner (conservative, proactive, and finer and flexible update in the congestion window) in order to reduce the contentions and congestion, thus improving the performance of TCP in AWNs. The key advantage of Learning-TCP is that, without relying on any network feedback such as explicit congestion and link-failure notifications, it adapts to the changing network conditions and appropriately updates the congestion window by observing the inter-arrival times of TCP acknowledgments. We implemented Learning-TCP in ns-2.28 and Linux kernel 2.6 as well, and evaluated its performance for a wide range of network conditions. In all the studies, we observed that Learning-TCP outperforms TCP-Newreno by showing significant improvement in the goodput and reduction in the packet loss while maintaining higher fairness to the competing flows.