多媒体传感器网络中多路径传输方式及其拥塞控制机制

提出一种多媒体传感器网络中的多路径传输方法.综合考虑传输时间、链路剩余能量及传输速率等因素,通过元数据分组的探寻,建立三类路径,并利用自适应采样时间间隔调整,降低了网络拥塞的可能性.实验表明,本方法在分组丢失率、传输实时性、拥塞控制等方面均表现出良好性能.     

基于反馈机制的自愈算法

提出了一种网络自愈算法,当网络中的节点发生故障或链路出现拥塞时,该算法利用Q学习的反馈机制、多QoS约束的评价函数和基于Boltzmann-Gibbs分布的路径选择策略,自适应地选择恢复路径,降低了选择发生故障和拥塞路径的概率,从而实现了自愈。仿真结果表明,该算法在恢复率、区分业务能力和网络资源优化等方面,表现出了良好的性能。     

基于Q学习的无线传感网络自愈算法

无线传感网络存在关键区域节点能量消耗过快,节点能量供应有限以及通信链路拥塞等问题,容易造成节点故障和路由破坏。为减小上述问题对网络传输造成的影响,提出一种基于Q学习的无线传感网络自愈算法,通过引入Q学习的反馈机制,动态感知网络的状态信息,当故障发生时,自适应地选择恢复路径,保证数据实时顺利传输。仿真结果表明,该算法降低了错误选择故障或拥塞路径的概率,在故障感知、故障恢复和延长网络寿命等方面,表现出了良好的性能。     

基于价格调整和流量工程的软件定义数据中心网络传输优化方法

分析数据中心网络动态价格调整拥塞控制和流量工程传输优化方法的研究现状,提出结合拥塞控制、流量调度和负载均衡的网络传输优化方法,设计一种新型数据中心网络资源动态价格调整策略框架,构建一种两层结构的数据中心网络拥塞控制价格设置算法,平衡和调节各发送端的购买力和链路带宽收益之间的关系,根据各价格指标设计具有QoS路由技术与调度算法实现资源优化利用的流量工程方法,扩展OpenFlow协议算法,整合SDN、FAST协议、ECN三种技术,从运行机制方面找到提高数据中心网络传输性能的方法.     

空间延迟/中断容忍网络拥塞控制策略研究

针对空间延迟/中断容忍网络（DTN, delay/disruption tolerant network）的拥塞控制问题,提出一种基于提前卸载的拥塞控制策略（EOCC,early offloading-based congestion control）。由于空间DTN网络大时延和不能保证时刻存在端到端路径的特点,EOCC主要利用网络节点的本地信息在拥塞发生前就采取措施。具体地,EOCC会时刻监测节点缓存变化速率,在即将发生拥塞时,将消息通过早于最优路径的非最优路径传输,从而缓解节点存储压力。仿真结果表明,采用EOCC的接触图路由获得了更好的性能。     

无线Ad hoc网络中的随机功率控制

 由于能量的限制,无线Ad hoc网络面临网络生存时间、无线资源利用效率以及时延要求等方面的挑战.无线Ad hoc网络中的功率控制已经成为研究领域中的一个热点,其主要目的是降低网络在分发数据包中的能量消耗,降低网络中的通信干扰.为了节省网络能量消耗,提出了一种随机功率控制的方法,其核心是让节点的发射功率随机分布在一个功率区间.通过对随机功率控制和固定功率控制在成功传输概率和网络节能上的理论分析和数值计算比较发现,合理选择随机功率控制中的最小发射功率,可获得与固定功率控制相当的成功传输概率,并能节省网络能量消耗,延长网络生存周期.     

分组交换网中拥塞控制的时间戳方法

本文提出了一种拥塞控制的时间戳方法，其基本思想是：网络每条路径设置一能够反映网络拥塞状况的状态参数，该参数通过阶段性地在源端和目的端交换携带延迟和吞吐量信息的样品包来获得，依据这些参数值判断网络状态，根据网络状态调整通信量，这种与路由选择相结合的拥塞控制方法，具有简单、开销小和易于实现的特点。     

HSDPA网络中基于虚拟队列的Iub流量控制

随着UMTSHSPA+技术的发展以及上下行峰值速率的不断增加,无线接入网络拥塞日益严重。由于底层重传协议的存在,TCP的拥塞控制方法不能有效解决HSDPA网络中的拥塞问题。3GPP定义了HSDPA流量控制算法,但该算法仅解决了空中接口的拥塞问题。本文提出了基于虚拟队列的流量控制方法,旨在解决Iub传输网络的拥塞问题。系统分析和性能仿真证明了该算法能有效地规避网络拥塞导致的RLC实体重传,从而提高Iub传输链路的吞吐量,并且传输时延和丢包的情况也不会恶化。此外,该算法可以针对运营商的具体服务质量(QoS)需求进行调节。     

基于拥塞预知的WSN多径寻优路由协议

针对无线传感器网络中常出现传输拥塞的问题,该文提出了一种基于拥塞预知的多径寻优路由协议(MOPC)。该协议基于主动避免拥塞的设计思想,依据节点的拥塞预知度、剩余能量和最小跳数建立路径满意度模型,实现了最优路径的选取;通过设定最优路径上节点的转发满意度变化率阈值,实现局部路由的动态维护。仿真结果表明,该协议具有良好的实时性和可靠性,并能显著提高能量利用率,延长网络生命期。     

最小化路径代价和流量均衡模型及算法

流量均衡是流量工程中为避免网络拥塞经常采用的路由优化目标,如何选择路径以使流量达到均衡分布是流量路由的研究热点和难点.为了最小化网络拥塞,该文在指出网络拥塞决定于流量路由时所选路径的拥塞特征后,建立了流量分布的最小化路径代价和模型.在流量路由选择路径时,提出基于瓶颈链路的最小代价路径路由算法.在实际的网络拓扑和流量矩阵数据基础上对所提模型及算法进行了实验验证,结果显示:在网络负载较大时最大链路利用率相对于已有模型可降低近20%.     

无线多跳网络快速跨层资源优化分配算法

针对背压路由算法容易造成大量队列积压和收敛速度慢的缺陷,该文研究了无线多跳网络中节点功率受限情况下的联合拥塞控制、路由和功率分配的跨层优化问题。以最大化网络效用为目标,以流平衡条件、功率等为约束条件建模,基于牛顿法提出了一种具有超线性收敛性能的算法,并运用矩阵分裂技术使该算法能够分布式实施。仿真结果表明,该算法在实现网络效用最大化的同时,能够有效提高网络中的能量效用,且能将网络中的队列长度稳定在一个较低水平,降低包传输延时。     

A Robust and Efficient Cross-Layer Optimal Design in Wireless Sensor Networks

When using wireless sensor networks (WSNs) for data transmission, some critical respects should be considered. These respects are limited computational power, storage capability and energy consumption. To save the energy in WSNs and prolong the network lifetime, we design for the signal control input, routing selection and capacity allocation by the optimization model based on compressed sensing (CS) framework. The reasonable optimization model is decomposed into three subsections for three layers in WSNs: congestion control in transport layer, scheduling in link layer and routing algorithm in network layer, respectively. These three functions interact and are regulated by congestion ratio so as to achieve a global optimality. Congestion control can be robust and stable by CS theory that a relatively small number of the projections for a sparse signal contain most of its salient information. Routing selection is abided by fair resource allocation principle. The resources can be allocated more and more to the channel in the case of not causing more severe congestion, which can avoid conservatively reducing resources allocation for eliminating congestion. Simulation results show the stability of our algorithm, the accurate ratio of CS, the throughput, as well as the necessity of considering congestion in WSNs.     

基于非合作博弈的联合功率与速率控制算法

在多媒体CDMA网络中,需要对用户的功率进行控制,既保证每个用户的QoS要求,又不增加对其它用户的干扰,同时还要对用户的数据速率进行控制,以避免拥塞。将功率和速率控制等效为一个具有N个用户的非合作博弈,用效用函数表征用户对系统服务质量的满意程度,用代价函数描述达到通信要求所消耗的无线资源,从而将联合功率与速率控制算法描述为最大化净效用函数（效用函数和代价函数之差）的过程,最终得到系统中各用户全局最佳数据传输速率和达到服务质量所需的最小发射功率组合,并证明了纳什均衡的存在性。     

Distributed congestion control strategy using network utility maximization theory in VANET

Cooperative vehicle safety system (CVSS) rely on periodical beacons to track neighboring vehicles.High traffic density often causes channel congestion,seriously damaging the performance of CVSS.Existing congestion control strategies aim to ensure the performance in network layer,without considering the service requirements of vehicles in different driving contexts.To solve the problem,a distributed congestion control strategy using network utility maximization (NUM) theory was proposed.First of all,the NUM model for channel resource allocation was introduced.A utility function reflecting vehicle’s safety requirements was proposed in the model.Then under the condition of fixed transmit powers,a optimization problem of channel resource allocation was proposed.Lastly,to solve the optimization problem,a distributed congestion control algorithm named utility-based rate congestion control (UBRCC) algorithm was designed,the algorithm worked out the optimal beaconing rate by updating vehicle’s congestion price,realizing the resource allocation according to vehicle’s safety requirements.Simulation results validate that UBRCC algorithm can efficiently control channel congestion,reduce transmission delay,ensure reliable data transmission and satisfies the requirements of safety applications.     

Balancing transport and physical Layers in wireless multihop networks: jointly optimal congestion control and power control

In a wireless network with multihop transmissions and interference-limited link rates, can we balance power control in the physical layer and congestion control in the transport layer to enhance the overall network performance while maintaining the architectural modularity between the layers? We answer this question by presenting a distributed power control algorithm that couples with existing transmission control protocols (TCPs) to increase end-to-end throughput and energy efficiency of the network. Under the rigorous framework of nonlinearly constrained utility maximization, we prove the convergence of this coupled algorithm to the global optimum of joint power control and congestion control, for both synchronized and asynchronous implementations. The rate of convergence is geometric and a desirable modularity between the transport and physical layers is maintained. In particular, when congestion control uses TCP Vegas, a simple utilization in the physical layer of the queueing delay information suffices to achieve the joint optimum. Analytic results and simulations illustrate other desirable properties of the proposed algorithm, including robustness to channel outage and to path loss estimation errors, and flexibility in trading off performance optimality for implementation simplicity. This work presents a step toward a systematic understanding of "layering" as "optimization decomposition," where the overall communication network is modeled by a generalized network utility maximization problem, each layer corresponds to a decomposed subproblem, and the interfaces among layers are quantified as the optimization variables coordinating the subproblems. In the case of the transport and physical layers, link congestion prices turn out to be the optimal "layering prices.".     

Joint Congestion Control, Routing, and MAC for Stability and Fairness in Wireless Networks

In this paper, we describe and analyze a joint scheduling, routing and congestion control mechanism for wireless networks, that asymptotically guarantees stability of the buffers and fair allocation of the network resources. The queue-lengths serve as common information to different layers of the network protocol stack. Our main contribution is to prove the asymptotic optimality of a primal-dual congestion controller, which is known to model different versions of transmission control protocol well.     

An Efficient Cross-Layer Optimization Algorithm for Data Transmission in Wireless Sensor Networks

In this paper, we propose a cross layer congestion optimization scheme for allocating the resources of wireless sensor networks to achieve maximization of network performance. The congestion control, routing selection, link capacity allocation, and power consumption are all taken account to yield an optimal scheme based on the Lagrangian optimization. The Lagrangian multiplier is adopted to adjust power consumption, congestion rate, routing selection and link capacity allocation, so that the network performance can be satisfied between the trade-off of efficiency and fairness of resource allocation. The proposed algorithm can significantly achieve the maximization of network performance in relieving the network congestion with less power consumption. Excellent simulation results are obtained to demonstrate our innovative idea, and show the efficiency of our proposed algorithm.     

Joint rate and power control algorithms for wireless networks

There is a fundamental tradeoff between power consumption, data transmission rates, and congestion levels in a wireless network. These three elements influence the performance of rate and power control strategies, and they need to be coordinated judiciously. This paper proposes dynamic rate and power control algorithms for distributed wireless networks that also account for the congestion levels in a network. The design is pursued by formulating state-space models with and without uncertain dynamics and by determining control signals that help meet certain performance criteria (such as robustness and desired levels of signal-to-interference ratio). Simulation results illustrate the performance of the proposed control schemes.     

基于跳到跳信息的卫星网络传输控制协议研究

设计了一种适用于卫星网络的传输控制协议TPSN。该协议使用异步跳到跳确认,快速恢复成段丢失数据,并采用基于检测窗口的端到端选择性否定应答(SNACK)机制,减少协议控制信息,保证数据可靠传输。在跳到跳可靠性保证机制基础上传输网络负载,实现在避免网络拥塞条件下高效利用网络带宽资源,并保证具有不同端到端往返时延的异种数据流之间的公平性。仿真结果表明TPSN能够在长延迟、误码率高、链路频繁切换的卫星网络中保证高效的带宽利用、可靠的数据传输以及各数据流之间的公平。     

H-CRAN网络下联合拥塞控制和资源分配的网络切片动态资源调度策略

针对异构云无线接入网络(H-CRAN)网络下基于网络切片的在线无线资源动态优化问题,该文通过综合考虑业务接入控制、拥塞控制、资源分配和复用,建立一个以最大化网络平均和吞吐量为目标,受限于基站(BS)发射功率、系统稳定性、不同切片的服务质量(QoS)需求和资源分配等约束的随机优化模型,并进而提出了一种联合拥塞控制和资源分配的网络切片动态资源调度算法。该算法会在每个资源调度时隙内动态地为性能需求各异的网络切片中的用户分配资源。仿真结果表明,该文算法能在满足各切片用户QoS需求和维持网络稳定的基础上,提升网络整体吞吐量,并且还可通过调整控制参量的取值实现时延和吞吐量间的动态平衡。