微通信元系统架构下的拥塞控制机制研究

在简述现存网络架构的技术弱点后,提出了微通信元系统架构的思想,微通信元体系结构对不同服务类型的数据构建不同的虚电路进行传输.针对这种数据通信策略,提出了一种基于反馈信息位的拥塞控制机制,该机制根据来自路由节点的反馈信息调整一个虚电路发送端的发送速率,以实现拥塞控制.NS仿真表明,此机制能有效提高网络的吞吐量,改善网络的性能.     

A Class of Cross‐Layer Optimization Design for Congestion and Energy Efficiency with Compressed Sensing in Wireless Sensing Networks

In wireless sensor networks (WSNs), the congestion problem not only causes packet loss, but also leads to an increase in delays and energy consumption. The actual performance of wireless sensor networks (WSNs) can be severely influenced by the quality of the communication channel and the bit in transmission. In this paper, the distributed protocols, which attain global optimum control for signals by the compressed sensing technique and achieve fair channel allocation by the scheduling algorithm, are proposed for WSNs. We take into account the congestion problem by robust optimization with congestion ratio for two classic aspects in energy limited WSNs: minimum transmission rate and maximum transmitted information. To achieve the goal, three protocols are developed. In the first protocol, the desired control input is designed based on the compressed sensing technique. A minimal bit of signal is provided to reduce the transmission flow for the congestion model. The second protocol is resource allocation. The resources can be allocated increasingly to the channel in order to avoid more severe congestion. This can also avoid conservative reduction of resource allocation for eliminating congestion. Channel selection abides by the fair resource allocation principle. The above protocols separately are implemented through a congestion ratio at network layer, transport layer, and MAC layer. Simulation results demonstrate that the proposed algorithm effectively relieves congestion, and achieves higher throughput and lower energy consumption.     

Ad hoc网络中的简单跨层流控机制

为了提高Ad hoc网络中传输层协议的性能,基于跨层思想设计了一种简单可行的跨层流控机制。该机制结合网络层路由反馈、传输层协议和应用层速率自适应调节,通过跨层信息交互,应用层可根据网络层反馈的路由信息来调节业务的发送速率,将网络负载维持在合理的水平以最大化网络吞吐量。计算机模拟评价表明该机制能改善基于UDP和TCP的业务性能,在网络负载较低的情况下效果尤为明显。     

3GPP中基于拥塞控制的协作DSR路由协议研究

针对现行的3GPP网络路由协议在路由选择时存在的可靠性低、路由开销大等问题,分析了网络中通信节点的工作状态,综合考虑协同合作方式的DSR路由机制和拥塞控制策略对3GPP网络性能的影响,提出了一种基于拥塞控制的增强型协作DSR路由协议,并通过3GPP网络系统级仿真验证改进后的协作路由协议的通信性能。仿真结果表明,所提的协作DSR协议显著提高了3GPP网络通信性能,在提高网络资源利用率的同时改善了数据传输的可靠性。     

CTC与网络编码的联合设计研究

Turbo码由于具有并行级联的特点,更易于与网络编码进行联合设计,迄今为止成为信道编码与网络编码联合设计领域的一个热点。在研究无线网络中物理层网络编码技术的基础上,提出了一种新型的物理层网络编码和信道编码的联合设计方案,即CTC码（卷积Turbo码）与网络编码的联合设计方案,该方案具有较小的译码时延,更强的纠错性能,对于移动台（MS）来说,不仅提高了码率,还比MS直接使用CTC编码的算法简单。仿真结果表明CTC-网络编码系统具有较强的纠错性能,更适合于各种恶劣环境下的通信。     

一种新的基于BP神经网络的拥塞控制算法

针对计算机高速互联网中发送端速率调节的问题,在一般网络模型基础上,将BP（Back Propagation神经网络运用到计算机网络的拥塞控制中,提出了一种基于BP神经网络的动态资源管理机制以解决网络的拥塞问题,对所提出的拥塞控制方案,进行了仿真分析,仿真结果显示,控制方案有较好的可扩展性,有效性,并使网络性能表现良好。     

基于干扰感知的无线自组网多播机制

在采用网络编码的无线自组网多播场景中,为了有效地克服节点密度较大时干扰对多播整体性能的影响,提出了一种衡量路径干扰情况的路由度量标准。基于该度量标准,对网络编码机会和节点间干扰避免进行了均衡处理,构建出一种基于部分网络编码的无线自组网干扰感知多播路由机制。仿真结果表明,该机制在能耗、延时和吞吐量等性能方面均优于基于传统网络编码的多播方案,因此特别适用于节点密度较大的场合。     

基于队列长度的自适应占空比MAC协议

由于无线传感器网络中设备电池能量有限,实现能量高效性是其主要考虑的问题。众所周知优秀的数据传输协议对降低能耗,延长网络生命周期有重要意义。而在基于竞争的MAC协议中,空闲监听是主要能量消耗来源,所以通常设计较低占空比的MAC协议来减少空闲监听时间。但是如果占空比过小,使得网络中所有数据传输集中在较短时间内,会导致节点无法完成所需要的通信。所以选择合适的节点占空比,对于资源受限的网络来说是一种很重要的节能方法。文中提出了一种新型的异步MAC协议QL-MAC,节点利用CSMA争用信道,发送一系列短的信标包唤醒目标节点,采用虚拟载波监听防止串听。不同于其他改变接收节点的方法,该协议从发送节点来考虑,可以根据缓冲区队列长度判断该网络负载,从而自适应调整节点的占空比,使节点及时发送数据,减少时延,并告知接收节点做出相应改变,进一步节省能量。在OMNET++上实现了QL-MAC协议,仿真结果表明QL-MAC协议展现了良好的时延和能量有效性。     

An end-connected dual bus topology for metropolitan area networks

We propose a new topology and the associated medium access protocol for Metropolitan Area Networks (MAN's). The network uses a dual bus with connected ends as the topology. The protocol uses a token passing scheme with destination stripping as the access mechanism. Additional transmissions, referred here as restricted transmissions are also included in the protocol. These transmissions are made possible by the end-connected topology. Using this scheme, a station can make use of even a reserved slot for transmission up to the reserving station on the bus. This mechanism considerably improves the network utilization over those of the conventional Distributed Queue Dual Bus (DQDB) and the Destination Stripping Dual Ring (DSDR) protocols. We carried out simulations to study the utilization and the delay characteristics of the proposed protocol under various network conditions. We demonstrate that the performance of the proposed protocol is much better than that of the DQDB with slot reuse.     

基于协议解析的工控网络安全仿真平台设计

工业控制网络的安全防护通常采用防火墙技术和多种复杂的应用层协议协同完成,但是未涉及应用层协议的深入分析。为了更好地保障工控网络数据访问的安全,结合工控网络报文定制性的特点,详细分析了基于应用层协议解析的安全防护策略。该方案在工业防火墙的基础上,通过对工控网络通信协议的报文深入解析,直接在报文层面解析过滤,从而拦截与功能实现无关的报文,并发现隐藏较深的威胁。以OPC协议为例,搭建了基于应用层协议深度解析的工控网络安全仿真测试平台,并利用石化企业现场设备的通信数据对该平台进行了验证。所提出的安防策略为工控网络安全设备的设计和制造提供了一种基于应用层协议解析的方案,具备较高级别的安全性能。     

基于自适应转发的大数据通信带宽时延感知拥塞控制技术

大数据通信带宽时延会导致通信拥塞故障,影响通信网络的正常运行,为此提出基于自适应转发的大数据通信带宽时延感知拥塞控制技术。根据通信网络的组成结构和通信原理,构建大数据通信网络模型。在该模型下,采集大数据通信带宽时延,通过特征提取与匹配,感知当前通信网络的拥塞状态。针对处于拥塞状态的通信信道,在考虑通信带宽的情况下,计算拥塞控制量,利用自适应转发技术调度并分配通信带宽,在差分流传输控制协议的支持下,实现大数据通信带宽时延感知拥塞控制。通过拥塞控制效果测试实验得出结论：与传统拥塞控制技术相比,在优化设计技术的控制作用下,移动通信网络的吞吐量有所增加,带宽时延降低了149.3ms,同时通信误码率降低了0.037%,即优化设计技术在拥塞控制效果方面具有明显优势。     

采用网络编码的广播传输效率分析

网络编码技术是一项近年来得到高度关注的新技术,它能提高网络带宽的利用率,增强网络传输的安全性,有效降低设备能耗.为此,建立一种无线网络模型,该模型包含一个发送节点和多个接收节点,并且增加了对ACK/NAK丢失出错情况的设计.制定了采用网络编码技术和不采用网络编码技术2种广播方案.通过对2种方案的理论分析和仿真结果表明,...     

An energy-efficient,transport-controlled MAC protocol for wireless sensor networks

In wireless sensor networks (WSNs), one major cause of wasted energy is that the wireless network interface is always on to accept possible traffic. Many medium access control (MAC) protocols therefore adopted a periodic listen-and-sleep scheme to save energy, at sacrifice of end-to-end latency and throughput. Another cause is packet dropping due to network congestion, necessitating a lightweight transport protocol for WSNs. In this paper, we suggest a transport-controlled MAC protocol (TC-MAC) that combines the transport protocol into the MAC protocol with the aims of achieving high performance as well as energy efficiency in multi-hop forwarding. Although TC-MAC also works through a periodic listen-and-sleep scheme, it lowers end-to-end latency by reserving data forwarding schedules across multi-hop nodes during the listen period and by forwarding data during the sleep period, all while increasing throughput by piggybacking the subsequent data forwarding schedule on current data transmissions and forwarding data consecutively. In addition, TC-MAC gives a fairness-aware lightweight transport control mechanism based on benefits of using the MAC-layer information. The results show that TC-MAC performs as well as an 802.11-like MAC in end-to-end latency and throughput, and is more efficient than S-MAC in energy consumption, with the additional advantage of supporting fairness-aware congestion control.     

A link layer adaptive pacing scheme for improving throughput of transport protocols in wireless mesh networks

In this paper, we study the performance of a static multihop wireless network, specifically that of the backhaul network of a two-tier Wireless Mesh Network (WMN) operating on IEEE 802.11 Medium Access Control (MAC) protocol. The performance of an IEEE 802.11 based backhaul network is greatly affected by the MAC contention and congestion in the network. If the sources pump data into the network than can be supported, loss rate increases due to MAC contention and congestion in the network. This also leads to the problem of unfairness among flows. In this paper, we propose a Link Layer Adaptive Pacing (LLAP) scheme that adaptively controls the offered load into the network. This improves the performance of higher layer protocols without any modifications to them. Our LLAP scheme estimates the four hop transmission delay in the network path without incurring any additional overhead (Control packets) and accordingly paces the packet transmissions to reduce MAC contentions in the network. We implement the LLAP scheme in ns-2.29 network simulator and extensively study its performance for both User Datagram Protocol (UDP) and Transmission Control Protocol (TCP) traffic in different network scenarios. In all the cases, our scheme shows a significant improvement in the performance of both UDP and TCP traffic.     

A novel data fusion scheme using grey model and extreme learning machine in wireless sensor networks

With the increasing presence and adoption of wireless sensor networks (WSNs), the demand of data acquisition and data fusion are becoming stronger and stronger. In WSN, sensor nodes periodically sense data and send them to the sink node. Since the network consists of plenty of low-cost sensor nodes with limited battery power and the sensed data usually are of high temporal redundancy, prediction- based data fusion has been put forward as an important issue to reduce the number of transmissions and save the energy of the sensor nodes. Considering the fact that the sensor node usually has limited capabilities of data processing and storage, a novel prediction-based data fusion scheme using grey model (GM) and optimally pruned extreme learning machine (OP-ELM) is proposed. The proposed data fusion scheme called GM-OP-ELM uses a dual prediction mechanism to keep the prediction data series at the sink node and sensor node synchronous. During the data fusion process, GM is introduced to initially predict the data of next period with a small number of data items, and an OPELM- based single-hidden layer feedforward network (SLFN) is used to make the initial predicted value approximate its true value with extremely fast speed. As a robust and fast neural network learning algorithm, OP-ELM can adaptively adjust the structure of the SLFN. Then, GM-OP-ELM can provide high prediction accuracy, low communication overhead, and good scalability. We evaluate the performance of GM-OP-ELM on three actual data sets that collected from 54 sensors deployed in the Intel Berkeley Research lab. Simulation results have shown that the proposed data fusion scheme can significantly reduce redundant transmissions and extend the lifetime of the whole network with low computational cost.     

针对逆向流的Reno和Vegas算法性能的仿真分析

网络拥塞已经成为制约网络发展和应用的一个瓶颈.在TCP中已经实现的Reno和Vegas均是基于端到端的拥塞控制算法,它们虽然减轻了前向路径上的拥塞程度,但不能改善后向路径上数据流拥塞所导致的诸如吞吐率、丢包率等网络性能降低这一状况.基于"包丢失是由于网络拥塞引起"的假定,利用OPNET网络仿真软件,建立了单个瓶颈网络,设定了吞吐量、丢包率以及拥塞窗口(cwnd)等参数,对Reno和Vegas两种算法在逆向流中的性能进行比较,分析影响网络吞吐量的因素.仿真结果表明,在非对称网络中,Reno比Vegas更灵活且更实用,后向路径上逆向流的拥塞会极大地降低Vegas的吞吐量,使得Vegas和Reno不能很好地兼容.     

无线环境下基于丢包区分算法的流媒体拥塞控制

无线环境中存在的链路质量以及切换等的问题严重影响了拥塞控制机制的性能,该文针对此问题,考虑到实际无线链路的差错控制对上层的影响,提出了一种新的基于(M,K)统计测量方式的端到端丢包区分算法,并基于此设计了适合于无线环境的流媒体拥塞控制机制(WTFRC)。通过NS模拟验证,相对于其他端到端丢包区分算法,该文提出的算法的准确度更高,WTFRC可以在实际的无线环境中保持良好的性能。     

网络流量系统的有限拍控制

应用控制理论方法讨论了ATM网络的ABR通信中基于速率反馈的流量控制问题.针对网络的传播时延提出了有限拍控制策略,使系统的响应在有限拍的时间内严格地到达稳态,从而使信源发送速率快速响应网络状态的变化,较好地克服了时延对流量控制快速性和稳定性的影响.该方法能有效地避免拥塞发生,同时降低信元丢失率,且结构简单.仿真结果验证了此算法的有效性.     

认知中继网络中的功率分配算法

无人机（Unmanned aerial vehicle, UAV）通信是当前无线通信领域的研究热点。为了保证地面移动端与UAV通信的可靠性,提出了基于空时块码（Space-time block code, STBC）的协作中继传输方案。为了提升频谱效率,本文利用认知无线电技术,于协作中继处分别采用放大转发(Amplify-and-forward, AF)和解码转发(Decode-and-forward, DF)两种协议进行传输,在主用户通信服务质量得到保证和认知用户传输功率受限的条件下,建立以认知中继网络的吞吐量最大化为目标函数的优化问题。采取拉格朗日乘子法与Karush-Kuhn-Tucker (KKT)条件相结合的方案来实现优化问题中最优功率的分配。最后,仿真结果不仅验证了所提方案的有效性,还表明了DF中继协议下认知中继网络的吞吐量优于AF中继协议。     

低开销的无线网络编码机会路由协议设计

针对基于无线Mesh网络编码的机会路由协议的节点转发冗余问题,从线性空间的角度对该类协议的信息传输过程进行建模与分析,提出一种基于动态冗余控制的无线Mesh网络编码机会路由协议。该协议利用零空间确认技术估计各节点的更新信息总量,根据更新总量动态调整节点转发冗余,通过引入转发优先级调度机制,避免不同的转发节点重复转发来自于相同线性空间的编码包。仿真实验结果显示,与经典的MORE协议相比,该协议能提高30％-100％的网络吞吐量,同时降低20％-45％的归一化开销。