移动性无线传感器网络吞吐量跨层优化

采用跨层优化方法,分析了移动性无线传感器网络点对点链路的吞吐量优化问题。首先推导出吞吐量的理论表达式;以最大化吞吐量为目标,采用一种基于分层优化的数学框架,分别得到物理层最优符号速率、最优调制星座体积和MAC层最优数据包长;在此基础上,通过联合优化物理层参数和MAC层参数实现了链路吞吐量的最大化;最后提出了一种基于节点间通信距离的自适应跨层优化策略。仿真结果表明,与传统的分层优化相比,跨层优化后链路的吞吐量性能得到了明显提高。     

WLAN跨层链路自适应机制

针对IEEE 802.11无线局域网（WLAN）标准并没有给出速率自适应机制的问题,提出了联合物理层与MAC层的跨层链路自适应机制CLLA。该机制在考虑信道干扰、区分碰撞丢失和噪声干扰丢失的前提下,分别对物理层和MAC层进行了数学描述,建立了以吞吐量为性能指标的两层参数之间的函数关系,自适应地选择发送速率以提高系统的吞吐量。仿真实验及与现有链路自适应机制的比较表明,提出的跨层链路自适应机制CLLA不仅能适应噪声干扰与信道的变化,而且明显地提高了系统的吞吐量。     

业务驱动的无线多媒体传感器网络跨层优化

由于无线多媒体传感器网络链路动态变化、节点移动、带宽和能量受限等特点,传统的分层协议及其局部优化很难保证整个网络性能最优。为实现无线传感器网络中多媒体业务保障服务质量(QoS),提出一种基于业务驱动和自反馈机制的无线多媒体传感器网络跨层优化策略。该策略按照保证QoS等级最高业务服务质量原则,自适应优化网络协议栈各层参数,并将优化后参数反馈给相应网络协议层,实现保证QoS的网络资源优化,仿真结果表明,该方法在综合物理层误码率和链路层数据帧丢失率的情况下,与传统网络分层协义相比,提高多媒体信息传输质量方面有一定优越性。     

一种集中式水下无线传感器网跨层调度协议

分析了水下无线传感器网络（WSNs）中单链路发射功率和距离与频率的关系,提出一种跨层的集中式调度方法,AP（access point）在网络中通过广播信标的形式收集估计各节点的时延和距离信息,在MAC层考虑水下链路延迟特点,对各链路进行调度减少冲突;节点在物理层通过自适应地改变节点发射功率和发射频率,减少能耗.仿真结果表明：所提方案在节省系统能量消耗的同时,能够减少碰撞,提高系统吞吐量.     

DVB-RCS网络中的跨层协议优化研究

由于DVB-RCS网络长传播延迟以及高误码率的特点,会造成所承载TCP业务的性能下降。传统的分层协议设计方式已经不适合这种动态变化的网络特点。采用跨层协议设计方式优化TCP协议性能。跨层设计方式结合了传输层上TCP协议的工作特点,MAC层的接入策略以及物理层上的自适应调制编码策略。仿真结果显示了跨层协议设计相对于传统协议设计方式性能上的优势。     

基于跨层议价博弈的认知无线电网络资源优化分配策略

如何合理分配有限的频谱资源是认知无线电网络的核心问题之一.通过对物理层功率控制和MAC层带宽分配需求的研究,建立以最大化系统吞吐量为目标的跨层优化模型.并在该模型的基础上设计一种基于跨层议价博弈的带宽与功率分配算法(Bandwidth and Power Allocation Algorithm-Cross Layer Bargaining Game,BPAA-CLBG).仿真结果表明该算法可以有效地提高认知无线电网络的频谱利用率,且在系统吞吐量方面较现有算法有明显的改善.     

移动Ad Hoc网络的跨层优化拥塞控制

基于网络协议层框架充分分析了TCP应用到Ad Hoc网络导致性能下降的原因,包括:物理层中易损耗的无线信道, MAC层中的过度竞争和不公平接入,网络层中节点移动引起的频繁路由失效,传输层中TCP采用的不合适机制,包括基于窗口的传输、基于数据包丢失的拥塞指示,拥塞窗口的慢启动和AIMD、对ACK自定时的依赖;提出了全新的适合Ad Hoc网络特性的跨层优化拥塞控制协议CCOC(cross-layer optimal congestion control).CCOC运用了跨层设计框架来改进MAC层的接入信道公平性、检测虚假链路失效、减少路由失效次数、加快路由切换后的重启动、运用SACK实现可靠传输和实施非线性优化论指导设计的自适应优化策略;描述了CCOC的协议体系结构;实施了详细的NS仿真实验,仿真结果表明,在几乎所有的仿真场景和移动环境下,CCOC比TCP和ATCP在许多重要性能指标,如吞吐量和公平性方面都有了明显的改进.     

移动Ad Hoc网络的跨层优化拥塞控制

基于网络协议层框架充分分析了TCP应用到Ad Hoc网络导致性能下降的原因,包括:物理层中易损耗的无线信道, MAC层中的过度竞争和不公平接入,网络层中节点移动引起的频繁路由失效,传输层中TCP采用的不合适机制,包括基于窗口的传输、基于数据包丢失的拥塞指示,拥塞窗口的慢启动和AIMD、对ACK自定时的依赖;提出了全新的适合Ad Hoc网络特性的跨层优化拥塞控制协议CCOC(cross-layer optimal congestion control).CCOC运用了跨层设计框架来改进MAC层的接入信道公平性、检测虚假链路失效、减少路由失效次数、加快路由切换后的重启动、运用SACK实现可靠传输和实施非线性优化论指导设计的自适应优化策略;描述了CCOC的协议体系结构;实施了详细的NS仿真实验,仿真结果表明,在几乎所有的仿真场景和移动环境下,CCOC比TCP和ATCP在许多重要性能指标,如吞吐量和公平性方面都有了明显的改进.     

分级跨层设计的宽带无线接入网QoS架构

针对当前跨层设计导致信号流向混乱和处理时延长等问题,提出一种新的分级跨层设计的宽带无线接入网QoS架构。该架构具有链路独立层、链路独立-链路依赖的业务接口与链路依赖层,并给出各分级内及接口的QoS管理结构及模块功能。其中,物理层和无线链路层构成的链路依赖层可实现链路对信道的自适应,IP层及其上的各层构成的链路独立层在链路独立-链路依赖接口,通过业务QoS参数与无线资源的映射实现端到端的自适应,信号流向简单且处理时延减小。仿真结果表明,该架构的资源利用率明显优于分层结构。     

宽带卫星网络中基于跨层设计的带宽分配研究

传统的带宽分配策略按照分层结构进行设计,集中在链路层解决问题,没有考虑动态变化的信道状态和所承载的数据流的QoS性能。基于跨层设计的思想,针对支持话音业务和Internet数据业务的卫星网络提出了一种基于跨层设计的带宽分配算法。该策略将应用层的业务特性和数据链路层的带宽分配策略以及物理层的信道状态进行跨层优化。主控站通过建立代价函数的方法将所有相关参数综合考虑,利用动态规划算法得到了最佳的带宽分配方案。数值结果表明：跨层设计方式可以适应变化的信道状态,并且同传统带宽分配算法比较,提高了Internet数据的有效吞吐量并且保持了话音业务的QoS要求。     

部分信道状态信息下MIMO-OFDM的跨层资源分配算法

针对跨层多用户多输入多输出-正交频分复用（MIMO-OFDM）系统,以系统最大吞吐量为目标,给出一种基于部分信道状态信息的跨层资源分配算法。该优化问题设计的目标函数包括功率限制、传输速率、子载波占用、不同业务的服务质量需求与数据链路层的队列状态信息等约束条件。在数据链路层存在有限缓存条件下,通过均值反馈模型描述信道状态信息的反馈过程,推导出相应的跨层资源分配准则。仿真结果表明,所提算法与现有方案相比,满足了不同业务用户的QoS要求,并获得了好的吞吐率,降低了丢包率。     

基于UWB的无线传感器网络跨层优化模型研究

跨层设计是提高无线传感器网络整体性能的一种有效方法。在综合考虑MAC层调度、物理层功率控制、网络层路由三方面因素的基础上,结合超宽带技术大带宽、低信号功率的特点,以实现网络最大数据传输速率为目标,构建了基于超宽带技术的无线传感器网络跨层优化模型。仿真实验表明：模型最优解可有效提高网络数据传输速率;物理层功率控制对优化结果有着至关重要的影响。这证明以构建、求解优化模型的方式解决跨层设计问题是切实可行的,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一条新的解决思路。     

Joint scheduling and routing algorithm with load balancing in wireless mesh network

Wireless mesh network (WMN) is a promising solution for last mile broadband internet access. Mesh nodes or mesh routers are connected via wireless links to form a multi-hop backbone infrastructure and improving throughput is the primary goal. While previous works mainly focused on either link level protocol design or complex mathematical model, in this paper, we investigate the performance gains from jointly optimizing scheduling and routing in a multi-radio, multi-channel and multi-hop wireless mesh network. Then, two optimization objectives are addressed by considering wireless media contention and spatial multiplexing. The first objective is to maximize throughput by exploiting spatial reuse while the second one is to ensure fairness among different links. We design a cross-layer algorithm by considering both MAC layer and network layer. Simulation results show that our joint optimization algorithm can significantly increase throughput as well as fairness.     

超宽带传感器网络跨层优化模型应用研究

跨层设计是提高无线传感器网络整体性能的一种有效方法。在综合考虑MAC层调度、物理层功率控制、网络层路由三方面因素的基础上,结合超宽带技术大带宽、低信号功率的特点,以实现网络最大数据传输速率为目标,构建了超宽带传感器网络跨层优化模型,并提出了适用于大规模网络的数据传输解决方法。实验结果表明,模型最优解可有效提高网络的数据传输速率,同时该优化模型还可用于解决大规模网络数据传输问题。这证明以构建、求解优化模型的方式解决跨层设计问题是切实可行的。     

Cross-layer optimization policy for QoS scheduling in computational grid

This paper presents a cross-layer quality of service (QoS) optimization policy for computational grid. Efficient QoS management is critical for computational grid to meet heterogeneity and dynamics of resources and users’ requirements. There are different QoS metrics at different layers of computational grid. To improve perceived QoS by end users over computational grid, QoS supports can be addressed in different layers, including application layer, collective layer, fabric layer and so forth. The paper tackles cross-layer grid QoS optimization as optimization decomposition, each layer corresponds to a decomposed subproblem. The proposed policy produces an optimal set of grid resources, service compositions and user's payments at the fabric layer, collective layer and application layer respectively to maximize global grid QoS. The cross-layer optimization problem decomposes into three subproblems: grid resource allocation problem, service composing and user satisfaction degree maximization problem, all of which interact through the optimal variables for capacities of grid resources and service demand. In order to coordinate the subproblems, cross-layer QoS feedback mechanism is established to ensure different layer interactions. The simulations are conducted to validate the efficiency of the proposed policy.     

Cross-layer transmission and energy scheduling under full-duplex energy harvesting wireless OFDM joint transmission能量收集无线OFDM联合传输中的传输与能量跨层调度

This paper studies the design of the optimal and online cross-layer transmission and energy schedulings for a full-duplex energy harvesting wireless orthogonal frequency division multiplexing (OFDM) joint transmissions. Supported by today’s power management integrated circuit, the full-duplex energy harvesting system becomes a reality, which can overcome the transmission time loss problem caused by the half-duplex constraint of the energy storage unit (ESU) in the serial Harvest-Store-Use system. However, its corresponding modeling is still unexplored. Therefore, the full-duplex energy harvesting system is first modeled and proved to be equivalent to a composition of energy behavior models of Harvest-Store-Use in fine-time granularity. Then, the convex optimization problem of cross-layer transmission and energy scheduling is formulated with the objective to maximize the sum of transmission throughput during successively multiple time units, which takes into account the temporal variance of energy harvesting rates and channel states, and the limited capacity of ESUs. The optimal power allocation with three dimensions of time, channel and antenna is solved by utilizing the dual decomposition method with the pre-known temporal variance, and the corresponding result of the system throughput provides the theoretical upper bound. Finally, to reduce the throughput degradation caused by channel state prediction errors, a non-convex online scheduling problem is formulated as the classical energy efficiency format. It is transformed into a convex optimization problem by exploiting the properties of fractional programming, and then, an efficiently iterative solution is designed. Numerical results show that the average throughput of the online algorithm is 24% greater than that of existing time-energy adaptive water-filling algorithm. The degradation of the average throughput is less than 19% with probability 90%, even as the channel prediction error reaches 20%. These results provide guidelines for the design and optimization for full-duplex energy harvesting joint transmission systems.     

Error-Resilient Video Encoding and Transmission in Multirate Wireless LANs

In this paper, we present a cross-layer approach for video transmission in wireless LANs that employs joint source and application-layer channel coding, together with rate adaptation at the wireless physical layer (PHY). While the purpose of adopting PHY rate adaptation in modern wireless LANs like the IEEE 802.11a/b is to maximize the throughput, in this paper we exploit this feature to increase the robustness of wireless video. More specifically, we investigate the impact of adapting the PHY transmission rate, thus changing the throughput and packet loss channel characteristics, on the rate-distortion performance of a transmitted video sequence. To evaluate the video quality at the decoder, we develop a cross-layer modeling framework that considers jointly the effect of application-layer joint source-channel coding (JSCC), error concealment, and the PHY transmission rate. The resulting models are used by an optimization algorithm that calculates the optimal JSCC allocation for each video frame, and PHY transmission rate for each outgoing transport packet. The comprehensive simulation results obtained with the H.264/AVC codec demonstrate considerable increase in the PSNR of the decoded video when compared with a system that employs separately JSCC and PHY rate adaptation. Furthermore, our performance analysis indicates that the optimal PHY transmission rate calculated by the proposed algorithm, can be significantly different when compared with rate adaptation algorithms that target throughput improvement.